commit bc7ace5e11aa46c36317f60defb94a4568d55c99 Author: ModelHub XC Date: Mon May 25 01:12:24 2026 +0800 初始化项目，由ModelHub XC社区提供模型 Model: haoranli-ml/NOBOS-lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_cope Source: Original Platform diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..0038507 --- /dev/null +++ b/.gitattributes @@ -0,0 +1,36 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs 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+wandb/offline-run-20260502_014721-1i7ubroa/run-1i7ubroa.wandb filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..3ac1f91 --- /dev/null +++ b/README.md @@ -0,0 +1,59 @@ +--- +library_name: transformers +license: gemma +base_model: google/gemma-2b +tags: +- generated_from_trainer +model-index: +- name: lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope + results: [] +--- + + + +# lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope + +This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on an unknown dataset. + +## Model description + +More information needed + +## Intended uses & limitations + +More information needed + +## Training and evaluation data + +More information needed + +## Training procedure + +### Training hyperparameters + +The following hyperparameters were used during training: +- learning_rate: 1e-05 +- train_batch_size: 4 +- eval_batch_size: 4 +- seed: 42 +- distributed_type: multi-GPU +- num_devices: 16 +- gradient_accumulation_steps: 4 +- total_train_batch_size: 256 +- total_eval_batch_size: 64 +- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08 +- lr_scheduler_type: cosine +- lr_scheduler_warmup_ratio: 0.1 +- training_steps: 1250 + +### Training results + + + +### Framework versions + +- Transformers 4.44.2 +- Pytorch 2.4.1+cu121 +- Datasets 2.20.0 +- Tokenizers 0.19.1 diff --git a/checkpoint-1000/config.json b/checkpoint-1000/config.json new file mode 100644 index 0000000..8ee9c1a --- /dev/null +++ b/checkpoint-1000/config.json @@ -0,0 +1,29 @@ +{ + "_name_or_path": "google/gemma-2b", + "architectures": [ + "GemmaForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": 2, + "eos_token_id": 1, + "head_dim": 256, + "hidden_act": "gelu", + "hidden_activation": null, + "hidden_size": 2048, + "initializer_range": 0.02, + 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"train_batch_size": 4, + "trial_name": null, + "trial_params": null +} diff --git a/checkpoint-875/training_args.bin b/checkpoint-875/training_args.bin new file mode 100644 index 0000000..bc31b2f --- /dev/null +++ b/checkpoint-875/training_args.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:726cdb8a8ce2c6583f1dc87b7e01fbbfbb853bba541198164f1fb9eae287bfa4 +size 5752 diff --git a/config.json b/config.json new file mode 100644 index 0000000..8ee9c1a --- /dev/null +++ b/config.json @@ -0,0 +1,29 @@ +{ + "_name_or_path": "google/gemma-2b", + "architectures": [ + "GemmaForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": 2, + "eos_token_id": 1, + "head_dim": 256, + "hidden_act": "gelu", + "hidden_activation": null, + "hidden_size": 2048, + "initializer_range": 0.02, + "intermediate_size": 16384, + "max_position_embeddings": 8192, + "model_type": "gemma", + "num_attention_heads": 8, + "num_hidden_layers": 18, + "num_key_value_heads": 1, + "pad_token_id": 0, + "rms_norm_eps": 1e-06, + "rope_scaling": null, + "rope_theta": 200000.0, + "torch_dtype": "float32", + "transformers_version": "4.44.2", + "use_cache": true, + "vocab_size": 256000 +} diff --git a/generation_config.json b/generation_config.json new file mode 100644 index 0000000..b2c002e --- /dev/null +++ b/generation_config.json @@ -0,0 +1,7 @@ +{ + "_from_model_config": true, + "bos_token_id": 2, + "eos_token_id": 1, + "pad_token_id": 0, + "transformers_version": "4.44.2" +} diff --git a/log.out b/log.out new file mode 100644 index 0000000..286b7d4 --- /dev/null +++ b/log.out @@ -0,0 +1,3191 @@ +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/transformers/utils/hub.py:127: FutureWarning: Using `TRANSFORMERS_CACHE` is deprecated and will be removed in v5 of Transformers. Use `HF_HOME` instead. + warnings.warn( +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/transformers/utils/hub.py:127: FutureWarning: Using `TRANSFORMERS_CACHE` is deprecated and will be removed in v5 of Transformers. Use `HF_HOME` instead. + warnings.warn( +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/transformers/utils/hub.py:127: FutureWarning: Using `TRANSFORMERS_CACHE` is deprecated and will be removed in v5 of Transformers. Use `HF_HOME` instead. + warnings.warn( +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/transformers/utils/hub.py:127: FutureWarning: Using `TRANSFORMERS_CACHE` is deprecated and will be removed in v5 of Transformers. Use `HF_HOME` instead. + warnings.warn( +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/transformers/utils/hub.py:127: FutureWarning: Using `TRANSFORMERS_CACHE` is deprecated and will be removed in v5 of Transformers. Use `HF_HOME` instead. + warnings.warn( +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/transformers/utils/hub.py:127: FutureWarning: Using `TRANSFORMERS_CACHE` is deprecated and will be removed in v5 of Transformers. Use `HF_HOME` instead. + warnings.warn( +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/transformers/utils/hub.py:127: FutureWarning: Using `TRANSFORMERS_CACHE` is deprecated and will be removed in v5 of Transformers. Use `HF_HOME` instead. + warnings.warn( +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/transformers/utils/hub.py:127: FutureWarning: Using `TRANSFORMERS_CACHE` is deprecated and will be removed in v5 of Transformers. Use `HF_HOME` instead. + warnings.warn( +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/transformers/utils/import_utils.py:575: FutureWarning: `is_torch_tpu_available` is deprecated and will be removed in 4.41.0. Please use the `is_torch_xla_available` instead. + warnings.warn( +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/transformers/utils/import_utils.py:575: FutureWarning: `is_torch_tpu_available` is deprecated and will be removed in 4.41.0. Please use the `is_torch_xla_available` instead. + warnings.warn( +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/transformers/utils/import_utils.py:575: FutureWarning: `is_torch_tpu_available` is deprecated and will be removed in 4.41.0. Please use the `is_torch_xla_available` instead. + warnings.warn( +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/transformers/utils/import_utils.py:575: FutureWarning: `is_torch_tpu_available` is deprecated and will be removed in 4.41.0. Please use the `is_torch_xla_available` instead. + warnings.warn( +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/transformers/utils/import_utils.py:575: FutureWarning: `is_torch_tpu_available` is deprecated and will be removed in 4.41.0. Please use the `is_torch_xla_available` instead. + warnings.warn( +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/transformers/utils/import_utils.py:575: FutureWarning: `is_torch_tpu_available` is deprecated and will be removed in 4.41.0. Please use the `is_torch_xla_available` instead. + warnings.warn( +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/transformers/utils/import_utils.py:575: FutureWarning: `is_torch_tpu_available` is deprecated and will be removed in 4.41.0. Please use the `is_torch_xla_available` instead. + warnings.warn( +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/transformers/utils/import_utils.py:575: FutureWarning: `is_torch_tpu_available` is deprecated and will be removed in 4.41.0. Please use the `is_torch_xla_available` instead. + warnings.warn( +05/02/2026 01:47:07 - WARNING - __main__ - Process rank: 2, device: cuda:2, n_gpu: 1distributed training: True, 16-bits training: False +05/02/2026 01:47:07 - WARNING - __main__ - Process rank: 3, device: cuda:3, n_gpu: 1distributed training: True, 16-bits training: False +05/02/2026 01:47:07 - WARNING - __main__ - Process rank: 5, device: cuda:5, n_gpu: 1distributed training: True, 16-bits training: False +05/02/2026 01:47:07 - WARNING - __main__ - Process rank: 1, device: cuda:1, n_gpu: 1distributed training: True, 16-bits training: False +05/02/2026 01:47:07 - WARNING - __main__ - Process rank: 7, device: cuda:7, n_gpu: 1distributed training: True, 16-bits training: False +05/02/2026 01:47:07 - WARNING - __main__ - Process rank: 6, device: cuda:6, n_gpu: 1distributed training: True, 16-bits training: False +05/02/2026 01:47:07 - WARNING - __main__ - Process rank: 4, device: cuda:4, n_gpu: 1distributed training: True, 16-bits training: False + Loading checkpoint shards: 0%| | 0/2 [00:00], +fsdp_config={'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, +fsdp_min_num_params=0, +fsdp_transformer_layer_cls_to_wrap=None, +full_determinism=False, +gradient_accumulation_steps=4, +gradient_checkpointing=True, +gradient_checkpointing_kwargs=None, +greater_is_better=None, +group_by_length=False, +half_precision_backend=auto, +hub_always_push=False, +hub_model_id=haoranli-ml/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope, +hub_private_repo=False, +hub_strategy=all_checkpoints, +hub_token=, +ignore_data_skip=False, +include_inputs_for_metrics=False, +include_num_input_tokens_seen=False, +include_tokens_per_second=False, +jit_mode_eval=False, +label_names=None, +label_smoothing_factor=0.0, +learning_rate=1e-05, +length_column_name=length, +load_best_model_at_end=False, +local_rank=0, +log_level=info, +log_level_replica=warning, +log_on_each_node=True, +logging_dir=/tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/runs/May02_01-47-03_orchard-flame-30, +logging_first_step=False, +logging_nan_inf_filter=True, +logging_steps=1.0, +logging_strategy=steps, +lr_scheduler_kwargs={}, +lr_scheduler_type=cosine, +max_grad_norm=1.0, +max_steps=1250, +metric_for_best_model=None, +min_lr_ratio=0.1, +mp_parameters=, +neftune_noise_alpha=None, +no_cuda=False, +num_train_epochs=3.0, +optim=adamw_torch, +optim_args=None, +optim_target_modules=None, +output_dir=/tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope, +overwrite_output_dir=False, +past_index=-1, +per_device_eval_batch_size=4, +per_device_train_batch_size=4, +prediction_loss_only=False, +push_to_hub=True, +push_to_hub_model_id=None, +push_to_hub_organization=None, +push_to_hub_token=, +ray_scope=last, +remove_unused_columns=False, +report_to=['wandb'], +restore_callback_states_from_checkpoint=False, +resume_from_checkpoint=None, +run_name=lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope, +save_on_each_node=False, +save_only_model=True, +save_safetensors=True, +save_steps=125, +save_strategy=steps, +save_total_limit=1, +seed=42, +seq_parallel_size=1, +skip_memory_metrics=True, +split_batches=None, +streaming_dataset=True, +tf32=None, +torch_compile=False, +torch_compile_backend=None, +torch_compile_mode=None, +torch_empty_cache_steps=None, +torchdynamo=None, +tpu_metrics_debug=False, +tpu_num_cores=None, +use_cpu=False, +use_ipex=False, +use_legacy_prediction_loop=False, +use_mps_device=False, +warmup_ratio=0.1, +warmup_steps=0, +weight_decay=0.1, +) +05/02/2026 01:47:08 - INFO - __main__ - Data arguments DataArguments(single_seq=False, per_device_max_tokens=65536, apply_instruct_masks=False) +05/02/2026 01:47:08 - INFO - __main__ - Additional arguments ScriptArguments(model_name_or_path='google/gemma-2b', config_overrides='rope_theta=200000', config_overrides_json='', config_name=None, tokenizer_name='google/gemma-2b', cache_dir=None, use_fast_tokenizer=False, model_revision='main', use_auth_token=False, tokenized_mds_train=['/project/flame/aviralku/haoranl4/datasets/prolong-gemma-parts/thestackv1_concat_by_repo-65536@0.3', '/project/flame/aviralku/haoranl4/datasets/prolong-gemma-parts/book-65536@0.3', '/project/flame/aviralku/haoranl4/datasets/prolong-gemma-parts/fineweb-edu@0.1', '/project/flame/aviralku/haoranl4/datasets/prolong-gemma-parts/fineweb-2023-50@0.1', '/project/flame/aviralku/haoranl4/datasets/prolong-gemma-parts/stackexchange@0.04', '/project/flame/aviralku/haoranl4/datasets/prolong-gemma-parts/dolmawiki@0.04', '/project/flame/aviralku/haoranl4/datasets/prolong-gemma-parts/tuluv2@0.03', '/project/flame/aviralku/haoranl4/datasets/prolong-gemma-parts/arxiv@0.03', '/project/flame/aviralku/haoranl4/datasets/prolong-gemma-parts/openwebmath@0.03', '/project/flame/aviralku/haoranl4/datasets/prolong-gemma-parts/textbooks@0.03'], tokenized_mds_validation=[], tokenized_mds_test=[], token_scaled_loss=False) +[INFO|tokenization_utils_base.py:2269] 2026-05-02 01:47:08,727 >> loading file tokenizer.model from cache at /tmp/hf_cache/models--google--gemma-2b/snapshots/9cf48e52b224239de00d483ec8eb84fb8d0f3a3a/tokenizer.model +[INFO|tokenization_utils_base.py:2269] 2026-05-02 01:47:08,727 >> loading file added_tokens.json from cache at None +[INFO|tokenization_utils_base.py:2269] 2026-05-02 01:47:08,727 >> loading file special_tokens_map.json from cache at /tmp/hf_cache/models--google--gemma-2b/snapshots/9cf48e52b224239de00d483ec8eb84fb8d0f3a3a/special_tokens_map.json +[INFO|tokenization_utils_base.py:2269] 2026-05-02 01:47:08,727 >> loading file tokenizer_config.json from cache at /tmp/hf_cache/models--google--gemma-2b/snapshots/9cf48e52b224239de00d483ec8eb84fb8d0f3a3a/tokenizer_config.json +[INFO|tokenization_utils_base.py:2269] 2026-05-02 01:47:08,727 >> loading file tokenizer.json from cache at /tmp/hf_cache/models--google--gemma-2b/snapshots/9cf48e52b224239de00d483ec8eb84fb8d0f3a3a/tokenizer.json + Loading checkpoint shards: 50%|█████ | 1/2 [00:01<00:01, 1.02s/it] Loading checkpoint shards: 100%|██████████| 2/2 [00:01<00:00, 1.79it/s] + Loading checkpoint shards: 50%|█████ | 1/2 [00:00<00:00, 1.03it/s][INFO|configuration_utils.py:733] 2026-05-02 01:47:09,486 >> loading configuration file config.json from cache at /tmp/hf_cache/models--google--gemma-2b/snapshots/9cf48e52b224239de00d483ec8eb84fb8d0f3a3a/config.json +[INFO|configuration_utils.py:800] 2026-05-02 01:47:09,487 >> Model config GemmaConfig { + "_name_or_path": "google/gemma-2b", + "architectures": [ + "GemmaForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": 2, + "eos_token_id": 1, + "head_dim": 256, + "hidden_act": "gelu", + "hidden_activation": null, + "hidden_size": 2048, + "initializer_range": 0.02, + "intermediate_size": 16384, + "max_position_embeddings": 8192, + "model_type": "gemma", + "num_attention_heads": 8, + "num_hidden_layers": 18, + "num_key_value_heads": 1, + "pad_token_id": 0, + "rms_norm_eps": 1e-06, + "rope_scaling": null, + "rope_theta": 10000.0, + "torch_dtype": "bfloat16", + "transformers_version": "4.44.2", + "use_cache": true, + "vocab_size": 256000 +} + +05/02/2026 01:47:09 - INFO - __main__ - Overriding config: rope_theta=200000 +05/02/2026 01:47:09 - INFO - __main__ - New config: GemmaConfig { + "_name_or_path": "google/gemma-2b", + "architectures": [ + "GemmaForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": 2, + "eos_token_id": 1, + "head_dim": 256, + "hidden_act": "gelu", + "hidden_activation": null, + "hidden_size": 2048, + "initializer_range": 0.02, + "intermediate_size": 16384, + "max_position_embeddings": 8192, + "model_type": "gemma", + "num_attention_heads": 8, + "num_hidden_layers": 18, + "num_key_value_heads": 1, + "pad_token_id": 0, + "rms_norm_eps": 1e-06, + "rope_scaling": null, + "rope_theta": 200000.0, + "torch_dtype": "bfloat16", + "transformers_version": "4.44.2", + "use_cache": true, + "vocab_size": 256000 +} + +05/02/2026 01:47:09 - INFO - __main__ - Using model class GemmaForCausalLM for model_type='gemma' +[INFO|modeling_utils.py:3678] 2026-05-02 01:47:09,488 >> loading weights file model.safetensors from cache at /tmp/hf_cache/models--google--gemma-2b/snapshots/9cf48e52b224239de00d483ec8eb84fb8d0f3a3a/model.safetensors.index.json +[INFO|configuration_utils.py:1038] 2026-05-02 01:47:09,491 >> Generate config GenerationConfig { + "bos_token_id": 2, + "eos_token_id": 1, + "pad_token_id": 0 +} + + Loading checkpoint shards: 100%|██████████| 2/2 [00:01<00:00, 2.18it/s] Loading checkpoint shards: 100%|██████████| 2/2 [00:01<00:00, 1.87it/s] + Loading checkpoint shards: 0%| | 0/2 [00:00> All model checkpoint weights were used when initializing GemmaForCausalLM. + +[INFO|modeling_utils.py:4515] 2026-05-02 01:47:10,409 >> All the weights of GemmaForCausalLM were initialized from the model checkpoint at google/gemma-2b. +If your task is similar to the task the model of the checkpoint was trained on, you can already use GemmaForCausalLM for predictions without further training. +[INFO|configuration_utils.py:993] 2026-05-02 01:47:10,466 >> loading configuration file generation_config.json from cache at /tmp/hf_cache/models--google--gemma-2b/snapshots/9cf48e52b224239de00d483ec8eb84fb8d0f3a3a/generation_config.json +[INFO|configuration_utils.py:1038] 2026-05-02 01:47:10,466 >> Generate config GenerationConfig { + "bos_token_id": 2, + "eos_token_id": 1, + "pad_token_id": 0 +} + +05/02/2026 01:47:10 - INFO - __main__ - Model: GemmaForCausalLM( + (model): GemmaModel( + (embed_tokens): Embedding(256000, 2048, padding_idx=0) + (layers): ModuleList( + (0-17): 18 x GemmaDecoderLayer( + (self_attn): GemmaAttention( + (q_proj): Linear(in_features=2048, out_features=2048, bias=False) + (k_proj): Linear(in_features=2048, out_features=256, bias=False) + (v_proj): Linear(in_features=2048, out_features=256, bias=False) + (o_proj): Linear(in_features=2048, out_features=2048, bias=False) + (rotary_emb): GemmaRotaryEmbedding() + (distributed_attn_func): DistributedAttention() + (distributed_varlen_attn_func): DistributedAttention() + ) + (mlp): GemmaMLP( + (gate_proj): Linear(in_features=2048, out_features=16384, bias=False) + (up_proj): Linear(in_features=2048, out_features=16384, bias=False) + (down_proj): Linear(in_features=16384, out_features=2048, bias=False) + (act_fn): PytorchGELUTanh() + ) + (input_layernorm): GemmaRMSNorm() + (post_attention_layernorm): GemmaRMSNorm() + ) + ) + (norm): GemmaRMSNorm() + ) + (lm_head): Linear(in_features=2048, out_features=256000, bias=False) +) +05/02/2026 01:47:14 - WARNING - streaming.base.dataset - Because `predownload` was not specified, it will default to 8*batch_size if batch_size is not None, otherwise 64. Prior to Streaming v0.7.0, `predownload` defaulted to max(batch_size, 256 * batch_size // num_canonical_nodes). +05/02/2026 01:47:14 - WARNING - streaming.base.dataset - Because `predownload` was not specified, it will default to 8*batch_size if batch_size is not None, otherwise 64. Prior to Streaming v0.7.0, `predownload` defaulted to max(batch_size, 256 * batch_size // num_canonical_nodes). +05/02/2026 01:47:14 - WARNING - streaming.base.dataset - Because `predownload` was not specified, it will default to 8*batch_size if batch_size is not None, otherwise 64. Prior to Streaming v0.7.0, `predownload` defaulted to max(batch_size, 256 * batch_size // num_canonical_nodes). +05/02/2026 01:47:14 - WARNING - streaming.base.dataset - Because `predownload` was not specified, it will default to 8*batch_size if batch_size is not None, otherwise 64. Prior to Streaming v0.7.0, `predownload` defaulted to max(batch_size, 256 * batch_size // num_canonical_nodes). +05/02/2026 01:47:14 - WARNING - streaming.base.dataset - Because `predownload` was not specified, it will default to 8*batch_size if batch_size is not None, otherwise 64. Prior to Streaming v0.7.0, `predownload` defaulted to max(batch_size, 256 * batch_size // num_canonical_nodes). +05/02/2026 01:47:14 - WARNING - streaming.base.dataset - Because `predownload` was not specified, it will default to 8*batch_size if batch_size is not None, otherwise 64. Prior to Streaming v0.7.0, `predownload` defaulted to max(batch_size, 256 * batch_size // num_canonical_nodes). +05/02/2026 01:47:14 - WARNING - streaming.base.dataset - Because `predownload` was not specified, it will default to 8*batch_size if batch_size is not None, otherwise 64. Prior to Streaming v0.7.0, `predownload` defaulted to max(batch_size, 256 * batch_size // num_canonical_nodes). +05/02/2026 01:47:14 - INFO - training.dataset - Loading datasets for training +05/02/2026 01:47:14 - INFO - training.dataset - Loading dataset from /project/flame/aviralku/haoranl4/datasets/prolong-gemma-parts/thestackv1_concat_by_repo-65536 with proportion 0.3 +05/02/2026 01:47:14 - INFO - training.dataset - Loading dataset from /project/flame/aviralku/haoranl4/datasets/prolong-gemma-parts/book-65536 with proportion 0.3 +05/02/2026 01:47:14 - INFO - training.dataset - Loading dataset from /project/flame/aviralku/haoranl4/datasets/prolong-gemma-parts/fineweb-edu with proportion 0.1 +05/02/2026 01:47:14 - INFO - training.dataset - Loading dataset from /project/flame/aviralku/haoranl4/datasets/prolong-gemma-parts/fineweb-2023-50 with proportion 0.1 +05/02/2026 01:47:14 - INFO - training.dataset - Loading dataset from /project/flame/aviralku/haoranl4/datasets/prolong-gemma-parts/stackexchange with proportion 0.04 +05/02/2026 01:47:14 - INFO - training.dataset - Loading dataset from /project/flame/aviralku/haoranl4/datasets/prolong-gemma-parts/dolmawiki with proportion 0.04 +05/02/2026 01:47:14 - INFO - training.dataset - Loading dataset from /project/flame/aviralku/haoranl4/datasets/prolong-gemma-parts/tuluv2 with proportion 0.03 +05/02/2026 01:47:14 - INFO - training.dataset - Loading dataset from /project/flame/aviralku/haoranl4/datasets/prolong-gemma-parts/arxiv with proportion 0.03 +05/02/2026 01:47:14 - INFO - training.dataset - Loading dataset from /project/flame/aviralku/haoranl4/datasets/prolong-gemma-parts/openwebmath with proportion 0.03 +05/02/2026 01:47:14 - INFO - training.dataset - Loading dataset from /project/flame/aviralku/haoranl4/datasets/prolong-gemma-parts/textbooks with proportion 0.03 +05/02/2026 01:47:14 - WARNING - streaming.base.dataset - Because `predownload` was not specified, it will default to 8*batch_size if batch_size is not None, otherwise 64. Prior to Streaming v0.7.0, `predownload` defaulted to max(batch_size, 256 * batch_size // num_canonical_nodes). +[WARNING|trainer.py:598] 2026-05-02 01:47:16,233 >> max_steps is given, it will override any value given in num_train_epochs +[WARNING|trainer.py:598] 2026-05-02 01:47:16,233 >> max_steps is given, it will override any value given in num_train_epochs +[WARNING|trainer.py:598] 2026-05-02 01:47:16,233 >> max_steps is given, it will override any value given in num_train_epochs +[WARNING|trainer.py:598] 2026-05-02 01:47:16,233 >> max_steps is given, it will override any value given in num_train_epochs +[WARNING|trainer.py:598] 2026-05-02 01:47:16,233 >> max_steps is given, it will override any value given in num_train_epochs +[WARNING|trainer.py:598] 2026-05-02 01:47:16,233 >> max_steps is given, it will override any value given in num_train_epochs +[WARNING|trainer.py:598] 2026-05-02 01:47:16,233 >> max_steps is given, it will override any value given in num_train_epochs +[WARNING|trainer.py:797] 2026-05-02 01:47:16,363 >> Use streaming dataloader for train +[WARNING|trainer.py:797] 2026-05-02 01:47:16,370 >> Use streaming dataloader for train +[WARNING|trainer.py:797] 2026-05-02 01:47:16,376 >> Use streaming dataloader for train +[WARNING|trainer.py:797] 2026-05-02 01:47:16,376 >> Use streaming dataloader for train +[WARNING|trainer.py:797] 2026-05-02 01:47:16,378 >> Use streaming dataloader for train +[WARNING|trainer.py:797] 2026-05-02 01:47:16,382 >> Use streaming dataloader for train +[WARNING|trainer.py:797] 2026-05-02 01:47:16,382 >> Use streaming dataloader for train +[WARNING|trainer.py:598] 2026-05-02 01:47:16,585 >> max_steps is given, it will override any value given in num_train_epochs +[INFO|trainer.py:648] 2026-05-02 01:47:16,585 >> Using auto half precision backend +[INFO|trainer.py:265] 2026-05-02 01:47:16,585 >> Initializing sequence parallel groups with size 1 +[WARNING|trainer.py:797] 2026-05-02 01:47:16,743 >> Use streaming dataloader for train +[INFO|trainer.py:2134] 2026-05-02 01:47:19,939 >> ***** Running training ***** +[INFO|trainer.py:2135] 2026-05-02 01:47:19,939 >> Num examples = 20,000 +[INFO|trainer.py:2136] 2026-05-02 01:47:19,939 >> Num Epochs = 1 +[INFO|trainer.py:2137] 2026-05-02 01:47:19,939 >> Instantaneous batch size per device = 4 +[INFO|trainer.py:2140] 2026-05-02 01:47:19,939 >> Total train batch size (w. parallel, distributed & accumulation) = 256 +[INFO|trainer.py:2141] 2026-05-02 01:47:19,939 >> Gradient Accumulation steps = 4 +[INFO|trainer.py:2142] 2026-05-02 01:47:19,939 >> Total optimization steps = 1,250 +[INFO|trainer.py:2143] 2026-05-02 01:47:19,939 >> Number of trainable parameters = 156,635,776 +[INFO|integration_utils.py:807] 2026-05-02 01:47:20,047 >> Automatic Weights & Biases logging enabled, to disable set os.environ["WANDB_DISABLED"] = "true" +05/02/2026 01:47:20 - WARNING - streaming.base.dataset - Because `num_canonical_nodes` was not specified, and `shuffle_algo` is py1e, it will default to be equal to physical nodes. Prior to Streaming v0.7.0, `num_canonical_nodes` defaulted to 64 * physical nodes. +05/02/2026 01:47:20 - WARNING - streaming.base.dataset - Because `shuffle_block_size` was not specified, it will default to max(4_000_000 // num_canonical_nodes, 1 << 18) if num_canonical_nodes is not None, otherwise 262144. Prior to Streaming v0.7.0, `shuffle_block_size` defaulted to 262144. +05/02/2026 01:47:20 - WARNING - streaming.base.dataset - Because `num_canonical_nodes` was not specified, and `shuffle_algo` is py1e, it will default to be equal to physical nodes. Prior to Streaming v0.7.0, `num_canonical_nodes` defaulted to 64 * physical nodes. +05/02/2026 01:47:20 - WARNING - streaming.base.dataset - Because `shuffle_block_size` was not specified, it will default to max(4_000_000 // num_canonical_nodes, 1 << 18) if num_canonical_nodes is not None, otherwise 262144. Prior to Streaming v0.7.0, `shuffle_block_size` defaulted to 262144. +05/02/2026 01:47:20 - WARNING - streaming.base.dataset - Because `num_canonical_nodes` was not specified, and `shuffle_algo` is py1e, it will default to be equal to physical nodes. Prior to Streaming v0.7.0, `num_canonical_nodes` defaulted to 64 * physical nodes. +05/02/2026 01:47:20 - WARNING - streaming.base.dataset - Because `shuffle_block_size` was not specified, it will default to max(4_000_000 // num_canonical_nodes, 1 << 18) if num_canonical_nodes is not None, otherwise 262144. Prior to Streaming v0.7.0, `shuffle_block_size` defaulted to 262144. +05/02/2026 01:47:20 - WARNING - streaming.base.dataset - Because `num_canonical_nodes` was not specified, and `shuffle_algo` is py1e, it will default to be equal to physical nodes. Prior to Streaming v0.7.0, `num_canonical_nodes` defaulted to 64 * physical nodes. +05/02/2026 01:47:20 - WARNING - streaming.base.dataset - Because `shuffle_block_size` was not specified, it will default to max(4_000_000 // num_canonical_nodes, 1 << 18) if num_canonical_nodes is not None, otherwise 262144. Prior to Streaming v0.7.0, `shuffle_block_size` defaulted to 262144. +05/02/2026 01:47:20 - WARNING - streaming.base.dataset - Because `num_canonical_nodes` was not specified, and `shuffle_algo` is py1e, it will default to be equal to physical nodes. Prior to Streaming v0.7.0, `num_canonical_nodes` defaulted to 64 * physical nodes. +05/02/2026 01:47:20 - WARNING - streaming.base.dataset - Because `shuffle_block_size` was not specified, it will default to max(4_000_000 // num_canonical_nodes, 1 << 18) if num_canonical_nodes is not None, otherwise 262144. Prior to Streaming v0.7.0, `shuffle_block_size` defaulted to 262144. +05/02/2026 01:47:20 - WARNING - streaming.base.dataset - Because `num_canonical_nodes` was not specified, and `shuffle_algo` is py1e, it will default to be equal to physical nodes. Prior to Streaming v0.7.0, `num_canonical_nodes` defaulted to 64 * physical nodes. +05/02/2026 01:47:20 - WARNING - streaming.base.dataset - Because `shuffle_block_size` was not specified, it will default to max(4_000_000 // num_canonical_nodes, 1 << 18) if num_canonical_nodes is not None, otherwise 262144. Prior to Streaming v0.7.0, `shuffle_block_size` defaulted to 262144. +05/02/2026 01:47:20 - WARNING - streaming.base.dataset - Because `num_canonical_nodes` was not specified, and `shuffle_algo` is py1e, it will default to be equal to physical nodes. Prior to Streaming v0.7.0, `num_canonical_nodes` defaulted to 64 * physical nodes. +05/02/2026 01:47:20 - WARNING - streaming.base.dataset - Because `shuffle_block_size` was not specified, it will default to max(4_000_000 // num_canonical_nodes, 1 << 18) if num_canonical_nodes is not None, otherwise 262144. Prior to Streaming v0.7.0, `shuffle_block_size` defaulted to 262144. +wandb: Tracking run with wandb version 0.17.3 +wandb: W&B syncing is set to `offline` in this directory. +wandb: Run `wandb online` or set WANDB_MODE=online to enable cloud syncing. +05/02/2026 01:47:27 - WARNING - streaming.base.dataset - Because `num_canonical_nodes` was not specified, and `shuffle_algo` is py1e, it will default to be equal to physical nodes. Prior to Streaming v0.7.0, `num_canonical_nodes` defaulted to 64 * physical nodes. +05/02/2026 01:47:27 - WARNING - streaming.base.dataset - Because `shuffle_block_size` was not specified, it will default to max(4_000_000 // num_canonical_nodes, 1 << 18) if num_canonical_nodes is not None, otherwise 262144. Prior to Streaming v0.7.0, `shuffle_block_size` defaulted to 262144. +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/utils/checkpoint.py:1399: FutureWarning: `torch.cpu.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cpu', args...)` instead. + with device_autocast_ctx, torch.cpu.amp.autocast(**cpu_autocast_kwargs), recompute_context: # type: ignore[attr-defined] +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/utils/checkpoint.py:1399: FutureWarning: `torch.cpu.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cpu', args...)` instead. + with device_autocast_ctx, torch.cpu.amp.autocast(**cpu_autocast_kwargs), recompute_context: # type: ignore[attr-defined] +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/utils/checkpoint.py:1399: FutureWarning: `torch.cpu.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cpu', args...)` instead. + with device_autocast_ctx, torch.cpu.amp.autocast(**cpu_autocast_kwargs), recompute_context: # type: ignore[attr-defined] +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/utils/checkpoint.py:1399: FutureWarning: `torch.cpu.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cpu', args...)` instead. + with device_autocast_ctx, torch.cpu.amp.autocast(**cpu_autocast_kwargs), recompute_context: # type: ignore[attr-defined] +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/utils/checkpoint.py:1399: FutureWarning: `torch.cpu.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cpu', args...)` instead. + with device_autocast_ctx, torch.cpu.amp.autocast(**cpu_autocast_kwargs), recompute_context: # type: ignore[attr-defined] +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/utils/checkpoint.py:1399: FutureWarning: `torch.cpu.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cpu', args...)` instead. + with device_autocast_ctx, torch.cpu.amp.autocast(**cpu_autocast_kwargs), recompute_context: # type: ignore[attr-defined] +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/utils/checkpoint.py:1399: FutureWarning: `torch.cpu.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cpu', args...)` instead. + with device_autocast_ctx, torch.cpu.amp.autocast(**cpu_autocast_kwargs), recompute_context: # type: ignore[attr-defined] +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/utils/checkpoint.py:1399: FutureWarning: `torch.cpu.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cpu', args...)` instead. + with device_autocast_ctx, torch.cpu.amp.autocast(**cpu_autocast_kwargs), recompute_context: # type: ignore[attr-defined] +[INFO|trainer.py:175] 2026-05-02 01:47:58,879 >> {'loss': 2.7873, 'grad_norm': 18.603376388549805, 'learning_rate': 8e-08, 'epoch': 0.0008, 'num_input_tokens_seen': 4194304, 'completed': '0.08% (1 / 1_250)', 'remaining time': '10:46:54', 'throughput': '101225.71', 'gpu_mem_free': '14314MB'} +[INFO|trainer.py:175] 2026-05-02 01:48:33,191 >> {'loss': 2.7398, 'grad_norm': 18.54471206665039, 'learning_rate': 1.6e-07, 'epoch': 0.0016, 'num_input_tokens_seen': 8388608, 'completed': '0.16% (2 / 1_250)', 'remaining time': '11:20:01', 'throughput': '122242.77', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 01:49:08,302 >> {'loss': 2.8373, 'grad_norm': 17.170970916748047, 'learning_rate': 2.4000000000000003e-07, 'epoch': 0.0024, 'num_input_tokens_seen': 12582912, 'completed': '0.24% (3 / 1_250)', 'remaining time': '11:36:14', 'throughput': '119456.17', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 01:49:43,515 >> {'loss': 2.8796, 'grad_norm': 18.720508575439453, 'learning_rate': 3.2e-07, 'epoch': 0.0032, 'num_input_tokens_seen': 16777216, 'completed': '0.32% (4 / 1_250)', 'remaining time': '11:44:34', 'throughput': '119113.25', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 01:50:18,930 >> {'loss': 2.7838, 'grad_norm': 17.71783447265625, 'learning_rate': 4.0000000000000003e-07, 'epoch': 0.004, 'num_input_tokens_seen': 20971520, 'completed': '0.40% (5 / 1_250)', 'remaining time': '11:50:10', 'throughput': '118433.89', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 01:50:49,651 >> {'loss': 2.942, 'grad_norm': 19.22686004638672, 'learning_rate': 4.800000000000001e-07, 'epoch': 0.0048, 'num_input_tokens_seen': 25165824, 'completed': '0.48% (6 / 1_250)', 'remaining time': '11:37:29', 'throughput': '136527.83', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 01:51:20,585 >> {'loss': 3.0736, 'grad_norm': 19.301416397094727, 'learning_rate': 5.6e-07, 'epoch': 0.0056, 'num_input_tokens_seen': 29360128, 'completed': '0.56% (7 / 1_250)', 'remaining time': '11:28:55', 'throughput': '135587.08', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 01:51:56,025 >> {'loss': 2.7353, 'grad_norm': 17.557605743408203, 'learning_rate': 6.4e-07, 'epoch': 0.0064, 'num_input_tokens_seen': 33554432, 'completed': '0.64% (8 / 1_250)', 'remaining time': '11:34:01', 'throughput': '118349.73', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 01:52:31,251 >> {'loss': 2.8516, 'grad_norm': 25.93338394165039, 'learning_rate': 7.2e-07, 'epoch': 0.0072, 'num_input_tokens_seen': 37748736, 'completed': '0.72% (9 / 1_250)', 'remaining time': '11:37:22', 'throughput': '119067.95', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 01:53:06,618 >> {'loss': 3.0769, 'grad_norm': 20.425596237182617, 'learning_rate': 8.000000000000001e-07, 'epoch': 0.008, 'num_input_tokens_seen': 41943040, 'completed': '0.80% (10 / 1_250)', 'remaining time': '11:40:13', 'throughput': '118595.72', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 01:53:42,173 >> {'loss': 3.1817, 'grad_norm': 33.30326843261719, 'learning_rate': 8.8e-07, 'epoch': 0.0088, 'num_input_tokens_seen': 46137344, 'completed': '0.88% (11 / 1_250)', 'remaining time': '11:42:47', 'throughput': '117965.18', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 01:54:17,383 >> {'loss': 2.9484, 'grad_norm': 18.383298873901367, 'learning_rate': 9.600000000000001e-07, 'epoch': 0.0096, 'num_input_tokens_seen': 50331648, 'completed': '0.96% (12 / 1_250)', 'remaining time': '11:44:14', 'throughput': '119124.28', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 01:54:52,876 >> {'loss': 2.996, 'grad_norm': 19.4766845703125, 'learning_rate': 1.04e-06, 'epoch': 0.0104, 'num_input_tokens_seen': 54525952, 'completed': '1.04% (13 / 1_250)', 'remaining time': '11:45:50', 'throughput': '118173.02', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 01:55:24,701 >> {'loss': 2.9518, 'grad_norm': 24.119272232055664, 'learning_rate': 1.12e-06, 'epoch': 0.0112, 'num_input_tokens_seen': 58720256, 'completed': '1.12% (14 / 1_250)', 'remaining time': '11:41:43', 'throughput': '131791.86', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 01:56:00,332 >> {'loss': 2.8631, 'grad_norm': 35.9194450378418, 'learning_rate': 1.2000000000000002e-06, 'epoch': 0.012, 'num_input_tokens_seen': 62914560, 'completed': '1.20% (15 / 1_250)', 'remaining time': '11:43:18', 'throughput': '117713.59', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 01:56:35,553 >> {'loss': 2.8866, 'grad_norm': 29.92550277709961, 'learning_rate': 1.28e-06, 'epoch': 0.0128, 'num_input_tokens_seen': 67108864, 'completed': '1.28% (16 / 1_250)', 'remaining time': '11:44:05', 'throughput': '119086.85', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 01:57:10,973 >> {'loss': 2.6439, 'grad_norm': 22.31702995300293, 'learning_rate': 1.3600000000000001e-06, 'epoch': 0.0136, 'num_input_tokens_seen': 71303168, 'completed': '1.36% (17 / 1_250)', 'remaining time': '11:44:56', 'throughput': '118415.64', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 01:57:46,465 >> {'loss': 2.8756, 'grad_norm': 18.49994659423828, 'learning_rate': 1.44e-06, 'epoch': 0.0144, 'num_input_tokens_seen': 75497472, 'completed': '1.44% (18 / 1_250)', 'remaining time': '11:45:44', 'throughput': '118174.91', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 01:58:20,559 >> {'loss': 2.6005, 'grad_norm': 13.499931335449219, 'learning_rate': 1.52e-06, 'epoch': 0.0152, 'num_input_tokens_seen': 79691776, 'completed': '1.52% (19 / 1_250)', 'remaining time': '11:44:51', 'throughput': '123021.98', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 01:58:56,127 >> {'loss': 2.8588, 'grad_norm': 14.18172836303711, 'learning_rate': 1.6000000000000001e-06, 'epoch': 0.016, 'num_input_tokens_seen': 83886080, 'completed': '1.60% (20 / 1_250)', 'remaining time': '11:45:31', 'throughput': '117924.37', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 01:59:28,015 >> {'loss': 2.693, 'grad_norm': 13.752593994140625, 'learning_rate': 1.6800000000000002e-06, 'epoch': 0.0168, 'num_input_tokens_seen': 88080384, 'completed': '1.68% (21 / 1_250)', 'remaining time': '11:42:29', 'throughput': '131531.67', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:00:03,370 >> {'loss': 2.4397, 'grad_norm': 11.675772666931152, 'learning_rate': 1.76e-06, 'epoch': 0.0176, 'num_input_tokens_seen': 92274688, 'completed': '1.76% (22 / 1_250)', 'remaining time': '11:42:54', 'throughput': '118636.32', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:00:38,686 >> {'loss': 2.327, 'grad_norm': 8.653132438659668, 'learning_rate': 1.8400000000000002e-06, 'epoch': 0.0184, 'num_input_tokens_seen': 96468992, 'completed': '1.84% (23 / 1_250)', 'remaining time': '11:43:11', 'throughput': '118764.38', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:01:13,857 >> {'loss': 2.436, 'grad_norm': 225.65805053710938, 'learning_rate': 1.9200000000000003e-06, 'epoch': 0.0192, 'num_input_tokens_seen': 100663296, 'completed': '1.92% (24 / 1_250)', 'remaining time': '11:43:17', 'throughput': '119253.03', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:01:49,088 >> {'loss': 2.585, 'grad_norm': 8.632149696350098, 'learning_rate': 2.0000000000000003e-06, 'epoch': 0.02, 'num_input_tokens_seen': 104857600, 'completed': '2.00% (25 / 1_250)', 'remaining time': '11:43:22', 'throughput': '119052.96', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:02:24,376 >> {'loss': 2.5949, 'grad_norm': 11.210970878601074, 'learning_rate': 2.08e-06, 'epoch': 0.0208, 'num_input_tokens_seen': 109051904, 'completed': '2.08% (26 / 1_250)', 'remaining time': '11:43:27', 'throughput': '118859.25', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:02:55,772 >> {'loss': 2.4227, 'grad_norm': 7.492502689361572, 'learning_rate': 2.16e-06, 'epoch': 0.0216, 'num_input_tokens_seen': 113246208, 'completed': '2.16% (27 / 1_250)', 'remaining time': '11:40:33', 'throughput': '133590.41', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:03:30,587 >> {'loss': 2.4561, 'grad_norm': 7.37083625793457, 'learning_rate': 2.24e-06, 'epoch': 0.0224, 'num_input_tokens_seen': 117440512, 'completed': '2.24% (28 / 1_250)', 'remaining time': '11:40:18', 'throughput': '120475.38', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:04:06,034 >> {'loss': 2.5057, 'grad_norm': 8.087807655334473, 'learning_rate': 2.3200000000000002e-06, 'epoch': 0.0232, 'num_input_tokens_seen': 121634816, 'completed': '2.32% (29 / 1_250)', 'remaining time': '11:40:28', 'throughput': '118327.89', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:04:41,047 >> {'loss': 2.2691, 'grad_norm': 7.973370552062988, 'learning_rate': 2.4000000000000003e-06, 'epoch': 0.024, 'num_input_tokens_seen': 125829120, 'completed': '2.40% (30 / 1_250)', 'remaining time': '11:40:18', 'throughput': '119792.14', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:05:16,463 >> {'loss': 2.2155, 'grad_norm': 6.233495235443115, 'learning_rate': 2.4800000000000004e-06, 'epoch': 0.0248, 'num_input_tokens_seen': 130023424, 'completed': '2.48% (31 / 1_250)', 'remaining time': '11:40:22', 'throughput': '118429.27', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:05:51,896 >> {'loss': 2.5236, 'grad_norm': 5.063961029052734, 'learning_rate': 2.56e-06, 'epoch': 0.0256, 'num_input_tokens_seen': 134217728, 'completed': '2.56% (32 / 1_250)', 'remaining time': '11:40:24', 'throughput': '118371.62', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:06:26,388 >> {'loss': 2.2936, 'grad_norm': 9.733742713928223, 'learning_rate': 2.64e-06, 'epoch': 0.0264, 'num_input_tokens_seen': 138412032, 'completed': '2.64% (33 / 1_250)', 'remaining time': '11:39:49', 'throughput': '121604.43', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:07:01,753 >> {'loss': 1.9985, 'grad_norm': 4.911775588989258, 'learning_rate': 2.7200000000000002e-06, 'epoch': 0.0272, 'num_input_tokens_seen': 142606336, 'completed': '2.72% (34 / 1_250)', 'remaining time': '11:39:45', 'throughput': '118599.34', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:07:36,295 >> {'loss': 2.1792, 'grad_norm': 3.896435022354126, 'learning_rate': 2.8000000000000003e-06, 'epoch': 0.028, 'num_input_tokens_seen': 146800640, 'completed': '2.80% (35 / 1_250)', 'remaining time': '11:39:11', 'throughput': '121427.19', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:08:11,730 >> {'loss': 1.9958, 'grad_norm': 3.778407573699951, 'learning_rate': 2.88e-06, 'epoch': 0.0288, 'num_input_tokens_seen': 150994944, 'completed': '2.88% (36 / 1_250)', 'remaining time': '11:39:07', 'throughput': '118365.23', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:08:47,083 >> {'loss': 2.2782, 'grad_norm': 9.616143226623535, 'learning_rate': 2.96e-06, 'epoch': 0.0296, 'num_input_tokens_seen': 155189248, 'completed': '2.96% (37 / 1_250)', 'remaining time': '11:38:59', 'throughput': '118638.97', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:09:22,413 >> {'loss': 2.1821, 'grad_norm': 19.738500595092773, 'learning_rate': 3.04e-06, 'epoch': 0.0304, 'num_input_tokens_seen': 159383552, 'completed': '3.04% (38 / 1_250)', 'remaining time': '11:38:49', 'throughput': '118720.18', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:09:57,927 >> {'loss': 2.1918, 'grad_norm': 3.59541392326355, 'learning_rate': 3.12e-06, 'epoch': 0.0312, 'num_input_tokens_seen': 163577856, 'completed': '3.12% (39 / 1_250)', 'remaining time': '11:38:43', 'throughput': '118101.28', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:10:33,351 >> {'loss': 2.093, 'grad_norm': 15.48968505859375, 'learning_rate': 3.2000000000000003e-06, 'epoch': 0.032, 'num_input_tokens_seen': 167772160, 'completed': '3.20% (40 / 1_250)', 'remaining time': '11:38:32', 'throughput': '118403.57', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:11:08,767 >> {'loss': 2.3892, 'grad_norm': 3653.303955078125, 'learning_rate': 3.2800000000000004e-06, 'epoch': 0.0328, 'num_input_tokens_seen': 171966464, 'completed': '3.28% (41 / 1_250)', 'remaining time': '11:38:21', 'throughput': '118429.35', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:11:43,967 >> {'loss': 2.1155, 'grad_norm': 32.1706657409668, 'learning_rate': 3.3600000000000004e-06, 'epoch': 0.0336, 'num_input_tokens_seen': 176160768, 'completed': '3.36% (42 / 1_250)', 'remaining time': '11:38:02', 'throughput': '119155.65', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:12:19,261 >> {'loss': 2.2692, 'grad_norm': 2.8586795330047607, 'learning_rate': 3.44e-06, 'epoch': 0.0344, 'num_input_tokens_seen': 180355072, 'completed': '3.44% (43 / 1_250)', 'remaining time': '11:37:44', 'throughput': '118840.33', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:12:54,605 >> {'loss': 2.0939, 'grad_norm': 2.559129238128662, 'learning_rate': 3.52e-06, 'epoch': 0.0352, 'num_input_tokens_seen': 184549376, 'completed': '3.52% (44 / 1_250)', 'remaining time': '11:37:28', 'throughput': '118671.48', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:13:30,070 >> {'loss': 2.054, 'grad_norm': 571.43017578125, 'learning_rate': 3.6000000000000003e-06, 'epoch': 0.036, 'num_input_tokens_seen': 188743680, 'completed': '3.60% (45 / 1_250)', 'remaining time': '11:37:14', 'throughput': '118264.20', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:14:05,284 >> {'loss': 1.9975, 'grad_norm': 3.4380502700805664, 'learning_rate': 3.6800000000000003e-06, 'epoch': 0.0368, 'num_input_tokens_seen': 192937984, 'completed': '3.68% (46 / 1_250)', 'remaining time': '11:36:52', 'throughput': '119109.17', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:14:40,737 >> {'loss': 2.0783, 'grad_norm': 5.3749589920043945, 'learning_rate': 3.7600000000000004e-06, 'epoch': 0.0376, 'num_input_tokens_seen': 197132288, 'completed': '3.76% (47 / 1_250)', 'remaining time': '11:36:36', 'throughput': '118306.30', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:15:12,204 >> {'loss': 1.7527, 'grad_norm': 4.685088157653809, 'learning_rate': 3.8400000000000005e-06, 'epoch': 0.0384, 'num_input_tokens_seen': 201326592, 'completed': '3.84% (48 / 1_250)', 'remaining time': '11:34:39', 'throughput': '133290.57', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:15:47,457 >> {'loss': 2.1694, 'grad_norm': 2.3193812370300293, 'learning_rate': 3.920000000000001e-06, 'epoch': 0.0392, 'num_input_tokens_seen': 205520896, 'completed': '3.92% (49 / 1_250)', 'remaining time': '11:34:18', 'throughput': '118978.42', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:16:22,790 >> {'loss': 1.9007, 'grad_norm': 2.4661011695861816, 'learning_rate': 4.000000000000001e-06, 'epoch': 0.04, 'num_input_tokens_seen': 209715200, 'completed': '4.00% (50 / 1_250)', 'remaining time': '11:33:59', 'throughput': '118708.52', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:16:58,121 >> {'loss': 1.9994, 'grad_norm': 2.252572774887085, 'learning_rate': 4.08e-06, 'epoch': 0.0408, 'num_input_tokens_seen': 213909504, 'completed': '4.08% (51 / 1_250)', 'remaining time': '11:33:39', 'throughput': '118715.22', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:17:33,262 >> {'loss': 1.9825, 'grad_norm': 1.9854445457458496, 'learning_rate': 4.16e-06, 'epoch': 0.0416, 'num_input_tokens_seen': 218103808, 'completed': '4.16% (52 / 1_250)', 'remaining time': '11:33:14', 'throughput': '119355.79', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:18:08,443 >> {'loss': 2.0662, 'grad_norm': 2.115206241607666, 'learning_rate': 4.24e-06, 'epoch': 0.0424, 'num_input_tokens_seen': 222298112, 'completed': '4.24% (53 / 1_250)', 'remaining time': '11:32:50', 'throughput': '119218.71', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:18:43,823 >> {'loss': 1.8202, 'grad_norm': 2.376163959503174, 'learning_rate': 4.32e-06, 'epoch': 0.0432, 'num_input_tokens_seen': 226492414, 'completed': '4.32% (54 / 1_250)', 'remaining time': '11:32:30', 'throughput': '118551.59', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:19:19,165 >> {'loss': 2.0107, 'grad_norm': 1.852526307106018, 'learning_rate': 4.4e-06, 'epoch': 0.044, 'num_input_tokens_seen': 230686718, 'completed': '4.40% (55 / 1_250)', 'remaining time': '11:32:08', 'throughput': '118679.00', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:19:54,607 >> {'loss': 2.0974, 'grad_norm': 1.7894747257232666, 'learning_rate': 4.48e-06, 'epoch': 0.0448, 'num_input_tokens_seen': 234881022, 'completed': '4.48% (56 / 1_250)', 'remaining time': '11:31:48', 'throughput': '118342.73', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:20:30,075 >> {'loss': 1.8972, 'grad_norm': 2.2246477603912354, 'learning_rate': 4.56e-06, 'epoch': 0.0456, 'num_input_tokens_seen': 239075326, 'completed': '4.56% (57 / 1_250)', 'remaining time': '11:31:28', 'throughput': '118254.27', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:21:05,371 >> {'loss': 1.9976, 'grad_norm': 1.827885389328003, 'learning_rate': 4.6400000000000005e-06, 'epoch': 0.0464, 'num_input_tokens_seen': 243269630, 'completed': '4.64% (58 / 1_250)', 'remaining time': '11:31:04', 'throughput': '118833.89', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:21:40,597 >> {'loss': 1.9973, 'grad_norm': 1.7587313652038574, 'learning_rate': 4.7200000000000005e-06, 'epoch': 0.0472, 'num_input_tokens_seen': 247463934, 'completed': '4.72% (59 / 1_250)', 'remaining time': '11:30:38', 'throughput': '119068.06', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:22:15,783 >> {'loss': 1.7249, 'grad_norm': 1.6262527704238892, 'learning_rate': 4.800000000000001e-06, 'epoch': 0.048, 'num_input_tokens_seen': 251658238, 'completed': '4.80% (60 / 1_250)', 'remaining time': '11:30:11', 'throughput': '119204.07', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:22:50,925 >> {'loss': 1.8767, 'grad_norm': 1.6403701305389404, 'learning_rate': 4.880000000000001e-06, 'epoch': 0.0488, 'num_input_tokens_seen': 255852542, 'completed': '4.88% (61 / 1_250)', 'remaining time': '11:29:43', 'throughput': '119350.46', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:23:21,672 >> {'loss': 2.0286, 'grad_norm': 4.19710111618042, 'learning_rate': 4.960000000000001e-06, 'epoch': 0.0496, 'num_input_tokens_seen': 260046846, 'completed': '4.96% (62 / 1_250)', 'remaining time': '11:27:50', 'throughput': '136414.80', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:23:56,995 >> {'loss': 1.7792, 'grad_norm': 1.3436150550842285, 'learning_rate': 5.04e-06, 'epoch': 0.0504, 'num_input_tokens_seen': 264241150, 'completed': '5.04% (63 / 1_250)', 'remaining time': '11:27:27', 'throughput': '118743.33', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:24:32,030 >> {'loss': 1.8584, 'grad_norm': 1.4033966064453125, 'learning_rate': 5.12e-06, 'epoch': 0.0512, 'num_input_tokens_seen': 268435454, 'completed': '5.12% (64 / 1_250)', 'remaining time': '11:26:57', 'throughput': '119715.47', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:25:06,265 >> {'loss': 1.5976, 'grad_norm': 1.3788018226623535, 'learning_rate': 5.2e-06, 'epoch': 0.052, 'num_input_tokens_seen': 272629758, 'completed': '5.20% (65 / 1_250)', 'remaining time': '11:26:13', 'throughput': '122517.51', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:25:41,605 >> {'loss': 1.9804, 'grad_norm': 1.4303852319717407, 'learning_rate': 5.28e-06, 'epoch': 0.0528, 'num_input_tokens_seen': 276824062, 'completed': '5.28% (66 / 1_250)', 'remaining time': '11:25:49', 'throughput': '118683.07', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:26:13,478 >> {'loss': 1.6747, 'grad_norm': 4.5790557861328125, 'learning_rate': 5.36e-06, 'epoch': 0.0536, 'num_input_tokens_seen': 281018366, 'completed': '5.36% (67 / 1_250)', 'remaining time': '11:24:23', 'throughput': '131594.12', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:26:48,625 >> {'loss': 1.8063, 'grad_norm': 1.4114742279052734, 'learning_rate': 5.4400000000000004e-06, 'epoch': 0.0544, 'num_input_tokens_seen': 285212670, 'completed': '5.44% (68 / 1_250)', 'remaining time': '11:23:56', 'throughput': '119336.81', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:27:24,074 >> {'loss': 1.8021, 'grad_norm': 1.2738819122314453, 'learning_rate': 5.5200000000000005e-06, 'epoch': 0.0552, 'num_input_tokens_seen': 289406974, 'completed': '5.52% (69 / 1_250)', 'remaining time': '11:23:34', 'throughput': '118317.65', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:27:59,195 >> {'loss': 2.0048, 'grad_norm': 1.3889662027359009, 'learning_rate': 5.600000000000001e-06, 'epoch': 0.056, 'num_input_tokens_seen': 293601278, 'completed': '5.60% (70 / 1_250)', 'remaining time': '11:23:06', 'throughput': '119424.02', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:28:34,550 >> {'loss': 1.8289, 'grad_norm': 1.1092036962509155, 'learning_rate': 5.68e-06, 'epoch': 0.0568, 'num_input_tokens_seen': 297795582, 'completed': '5.68% (71 / 1_250)', 'remaining time': '11:22:41', 'throughput': '118635.81', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:29:09,914 >> {'loss': 1.523, 'grad_norm': 1.075810194015503, 'learning_rate': 5.76e-06, 'epoch': 0.0576, 'num_input_tokens_seen': 301989886, 'completed': '5.76% (72 / 1_250)', 'remaining time': '11:22:17', 'throughput': '118601.94', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:29:45,071 >> {'loss': 1.6831, 'grad_norm': 1.0254493951797485, 'learning_rate': 5.84e-06, 'epoch': 0.0584, 'num_input_tokens_seen': 306184190, 'completed': '5.84% (73 / 1_250)', 'remaining time': '11:21:49', 'throughput': '119304.05', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:30:20,344 >> {'loss': 1.9048, 'grad_norm': 0.9615299105644226, 'learning_rate': 5.92e-06, 'epoch': 0.0592, 'num_input_tokens_seen': 310378494, 'completed': '5.92% (74 / 1_250)', 'remaining time': '11:21:22', 'throughput': '118908.87', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:30:55,477 >> {'loss': 1.8878, 'grad_norm': 1.1490670442581177, 'learning_rate': 6e-06, 'epoch': 0.06, 'num_input_tokens_seen': 314572798, 'completed': '6.00% (75 / 1_250)', 'remaining time': '11:20:53', 'throughput': '119384.81', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:31:30,744 >> {'loss': 1.8746, 'grad_norm': 0.8329099416732788, 'learning_rate': 6.08e-06, 'epoch': 0.0608, 'num_input_tokens_seen': 318767102, 'completed': '6.08% (76 / 1_250)', 'remaining time': '11:20:26', 'throughput': '118930.21', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:32:06,198 >> {'loss': 1.7206, 'grad_norm': 0.7526828050613403, 'learning_rate': 6.16e-06, 'epoch': 0.0616, 'num_input_tokens_seen': 322961406, 'completed': '6.16% (77 / 1_250)', 'remaining time': '11:20:02', 'throughput': '118300.75', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:32:39,532 >> {'loss': 1.928, 'grad_norm': 0.7630408406257629, 'learning_rate': 6.24e-06, 'epoch': 0.0624, 'num_input_tokens_seen': 327155710, 'completed': '6.24% (78 / 1_250)', 'remaining time': '11:19:05', 'throughput': '125825.81', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:33:14,803 >> {'loss': 1.7025, 'grad_norm': 0.761096179485321, 'learning_rate': 6.3200000000000005e-06, 'epoch': 0.0632, 'num_input_tokens_seen': 331350014, 'completed': '6.32% (79 / 1_250)', 'remaining time': '11:18:38', 'throughput': '118918.17', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:33:50,103 >> {'loss': 1.9139, 'grad_norm': 0.6824042201042175, 'learning_rate': 6.4000000000000006e-06, 'epoch': 0.064, 'num_input_tokens_seen': 335544318, 'completed': '6.40% (80 / 1_250)', 'remaining time': '11:18:11', 'throughput': '118820.54', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:34:25,637 >> {'loss': 1.8722, 'grad_norm': 0.8490806818008423, 'learning_rate': 6.480000000000001e-06, 'epoch': 0.0648, 'num_input_tokens_seen': 339738622, 'completed': '6.48% (81 / 1_250)', 'remaining time': '11:17:47', 'throughput': '118035.67', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:35:00,665 >> {'loss': 1.782, 'grad_norm': 0.6628430485725403, 'learning_rate': 6.560000000000001e-06, 'epoch': 0.0656, 'num_input_tokens_seen': 343932926, 'completed': '6.56% (82 / 1_250)', 'remaining time': '11:17:15', 'throughput': '119741.53', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:35:36,077 >> {'loss': 1.6204, 'grad_norm': 2.681325674057007, 'learning_rate': 6.640000000000001e-06, 'epoch': 0.0664, 'num_input_tokens_seen': 348127230, 'completed': '6.64% (83 / 1_250)', 'remaining time': '11:16:49', 'throughput': '118441.58', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:36:11,396 >> {'loss': 1.7727, 'grad_norm': 0.6645686030387878, 'learning_rate': 6.720000000000001e-06, 'epoch': 0.0672, 'num_input_tokens_seen': 352321534, 'completed': '6.72% (84 / 1_250)', 'remaining time': '11:16:22', 'throughput': '118753.81', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:36:43,556 >> {'loss': 1.6722, 'grad_norm': 0.7761685848236084, 'learning_rate': 6.800000000000001e-06, 'epoch': 0.068, 'num_input_tokens_seen': 356515838, 'completed': '6.80% (85 / 1_250)', 'remaining time': '11:15:11', 'throughput': '130422.77', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:37:17,573 >> {'loss': 1.9001, 'grad_norm': 0.5983083844184875, 'learning_rate': 6.88e-06, 'epoch': 0.0688, 'num_input_tokens_seen': 360710142, 'completed': '6.88% (86 / 1_250)', 'remaining time': '11:14:26', 'throughput': '123298.49', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:37:52,608 >> {'loss': 1.589, 'grad_norm': 0.6898380517959595, 'learning_rate': 6.96e-06, 'epoch': 0.0696, 'num_input_tokens_seen': 364904446, 'completed': '6.96% (87 / 1_250)', 'remaining time': '11:13:55', 'throughput': '119719.41', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:38:27,893 >> {'loss': 1.9512, 'grad_norm': 0.597122311592102, 'learning_rate': 7.04e-06, 'epoch': 0.0704, 'num_input_tokens_seen': 369098750, 'completed': '7.04% (88 / 1_250)', 'remaining time': '11:13:27', 'throughput': '118867.82', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:39:03,330 >> {'loss': 1.6029, 'grad_norm': 0.8148848414421082, 'learning_rate': 7.1200000000000004e-06, 'epoch': 0.0712, 'num_input_tokens_seen': 373293054, 'completed': '7.12% (89 / 1_250)', 'remaining time': '11:13:00', 'throughput': '118358.06', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:39:38,532 >> {'loss': 1.6555, 'grad_norm': 0.5283198952674866, 'learning_rate': 7.2000000000000005e-06, 'epoch': 0.072, 'num_input_tokens_seen': 377487358, 'completed': '7.20% (90 / 1_250)', 'remaining time': '11:12:31', 'throughput': '119150.05', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:40:14,059 >> {'loss': 1.6543, 'grad_norm': 0.7009382843971252, 'learning_rate': 7.280000000000001e-06, 'epoch': 0.0728, 'num_input_tokens_seen': 381681662, 'completed': '7.28% (91 / 1_250)', 'remaining time': '11:12:06', 'throughput': '118059.71', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:40:49,425 >> {'loss': 1.6511, 'grad_norm': 0.5229660868644714, 'learning_rate': 7.360000000000001e-06, 'epoch': 0.0736, 'num_input_tokens_seen': 385875966, 'completed': '7.36% (92 / 1_250)', 'remaining time': '11:11:38', 'throughput': '118599.43', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:41:24,639 >> {'loss': 1.6509, 'grad_norm': 0.6919147372245789, 'learning_rate': 7.440000000000001e-06, 'epoch': 0.0744, 'num_input_tokens_seen': 390070270, 'completed': '7.44% (93 / 1_250)', 'remaining time': '11:11:09', 'throughput': '119107.59', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:41:55,321 >> {'loss': 1.7527, 'grad_norm': 0.4472116529941559, 'learning_rate': 7.520000000000001e-06, 'epoch': 0.0752, 'num_input_tokens_seen': 394264574, 'completed': '7.52% (94 / 1_250)', 'remaining time': '11:09:43', 'throughput': '136703.75', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:42:30,660 >> {'loss': 1.9195, 'grad_norm': 0.6256005167961121, 'learning_rate': 7.600000000000001e-06, 'epoch': 0.076, 'num_input_tokens_seen': 398458878, 'completed': '7.60% (95 / 1_250)', 'remaining time': '11:09:15', 'throughput': '118687.39', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:43:05,707 >> {'loss': 1.7379, 'grad_norm': 0.5502773523330688, 'learning_rate': 7.680000000000001e-06, 'epoch': 0.0768, 'num_input_tokens_seen': 402653182, 'completed': '7.68% (96 / 1_250)', 'remaining time': '11:08:44', 'throughput': '119675.45', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:43:41,066 >> {'loss': 1.6649, 'grad_norm': 0.48381030559539795, 'learning_rate': 7.76e-06, 'epoch': 0.0776, 'num_input_tokens_seen': 406847486, 'completed': '7.76% (97 / 1_250)', 'remaining time': '11:08:16', 'throughput': '118621.02', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:44:15,397 >> {'loss': 1.7753, 'grad_norm': 0.5748535990715027, 'learning_rate': 7.840000000000001e-06, 'epoch': 0.0784, 'num_input_tokens_seen': 411041790, 'completed': '7.84% (98 / 1_250)', 'remaining time': '11:07:36', 'throughput': '122171.21', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:44:46,479 >> {'loss': 1.838, 'grad_norm': 0.46816733479499817, 'learning_rate': 7.92e-06, 'epoch': 0.0792, 'num_input_tokens_seen': 415236094, 'completed': '7.92% (99 / 1_250)', 'remaining time': '11:06:18', 'throughput': '134944.04', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:45:21,695 >> {'loss': 1.784, 'grad_norm': 0.514583945274353, 'learning_rate': 8.000000000000001e-06, 'epoch': 0.08, 'num_input_tokens_seen': 419430398, 'completed': '8.00% (100 / 1_250)', 'remaining time': '11:05:49', 'throughput': '119102.49', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:45:57,162 >> {'loss': 1.567, 'grad_norm': 0.5901820659637451, 'learning_rate': 8.08e-06, 'epoch': 0.0808, 'num_input_tokens_seen': 423624702, 'completed': '8.08% (101 / 1_250)', 'remaining time': '11:05:23', 'throughput': '118258.20', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:46:28,099 >> {'loss': 1.793, 'grad_norm': 0.5008239150047302, 'learning_rate': 8.16e-06, 'epoch': 0.0816, 'num_input_tokens_seen': 427819006, 'completed': '8.16% (102 / 1_250)', 'remaining time': '11:04:05', 'throughput': '135577.87', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:46:59,550 >> {'loss': 1.7547, 'grad_norm': 0.6191208958625793, 'learning_rate': 8.24e-06, 'epoch': 0.0824, 'num_input_tokens_seen': 432013310, 'completed': '8.24% (103 / 1_250)', 'remaining time': '11:02:54', 'throughput': '133357.48', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:47:34,074 >> {'loss': 1.4651, 'grad_norm': 0.4567963182926178, 'learning_rate': 8.32e-06, 'epoch': 0.0832, 'num_input_tokens_seen': 436207614, 'completed': '8.32% (104 / 1_250)', 'remaining time': '11:02:18', 'throughput': '121492.44', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:48:09,485 >> {'loss': 1.7321, 'grad_norm': 0.5242559909820557, 'learning_rate': 8.400000000000001e-06, 'epoch': 0.084, 'num_input_tokens_seen': 440401918, 'completed': '8.40% (105 / 1_250)', 'remaining time': '11:01:51', 'throughput': '118443.55', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:48:44,800 >> {'loss': 1.7021, 'grad_norm': 0.5472025275230408, 'learning_rate': 8.48e-06, 'epoch': 0.0848, 'num_input_tokens_seen': 444596222, 'completed': '8.48% (106 / 1_250)', 'remaining time': '11:01:23', 'throughput': '118768.84', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:49:19,968 >> {'loss': 1.5556, 'grad_norm': 0.9515178203582764, 'learning_rate': 8.560000000000001e-06, 'epoch': 0.0856, 'num_input_tokens_seen': 448790526, 'completed': '8.56% (107 / 1_250)', 'remaining time': '11:00:54', 'throughput': '119266.44', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:49:55,371 >> {'loss': 1.6477, 'grad_norm': 0.4213493764400482, 'learning_rate': 8.64e-06, 'epoch': 0.0864, 'num_input_tokens_seen': 452984830, 'completed': '8.64% (108 / 1_250)', 'remaining time': '11:00:27', 'throughput': '118471.93', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:50:30,688 >> {'loss': 1.588, 'grad_norm': 0.4360656142234802, 'learning_rate': 8.720000000000001e-06, 'epoch': 0.0872, 'num_input_tokens_seen': 457179134, 'completed': '8.72% (109 / 1_250)', 'remaining time': '10:59:58', 'throughput': '118761.72', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:51:05,047 >> {'loss': 1.5428, 'grad_norm': 0.364366352558136, 'learning_rate': 8.8e-06, 'epoch': 0.088, 'num_input_tokens_seen': 461373438, 'completed': '8.80% (110 / 1_250)', 'remaining time': '10:59:20', 'throughput': '122074.89', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:51:40,569 >> {'loss': 1.6836, 'grad_norm': 0.4667885899543762, 'learning_rate': 8.880000000000001e-06, 'epoch': 0.0888, 'num_input_tokens_seen': 465567742, 'completed': '8.88% (111 / 1_250)', 'remaining time': '10:58:54', 'throughput': '118074.53', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:52:15,586 >> {'loss': 1.5704, 'grad_norm': 0.8687509894371033, 'learning_rate': 8.96e-06, 'epoch': 0.0896, 'num_input_tokens_seen': 469762046, 'completed': '8.96% (112 / 1_250)', 'remaining time': '10:58:22', 'throughput': '119780.19', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:52:50,937 >> {'loss': 1.7097, 'grad_norm': 0.5468523502349854, 'learning_rate': 9.040000000000002e-06, 'epoch': 0.0904, 'num_input_tokens_seen': 473956350, 'completed': '9.04% (113 / 1_250)', 'remaining time': '10:57:54', 'throughput': '118647.25', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:53:26,326 >> {'loss': 1.5987, 'grad_norm': 0.8625032901763916, 'learning_rate': 9.12e-06, 'epoch': 0.0912, 'num_input_tokens_seen': 478150654, 'completed': '9.12% (114 / 1_250)', 'remaining time': '10:57:26', 'throughput': '118519.45', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:53:57,982 >> {'loss': 1.6045, 'grad_norm': 0.5430419445037842, 'learning_rate': 9.200000000000002e-06, 'epoch': 0.092, 'num_input_tokens_seen': 482344958, 'completed': '9.20% (115 / 1_250)', 'remaining time': '10:56:21', 'throughput': '132496.22', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:54:33,427 >> {'loss': 1.5655, 'grad_norm': 0.4539751410484314, 'learning_rate': 9.280000000000001e-06, 'epoch': 0.0928, 'num_input_tokens_seen': 486539262, 'completed': '9.28% (116 / 1_250)', 'remaining time': '10:55:53', 'throughput': '118334.14', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:55:08,583 >> {'loss': 1.6051, 'grad_norm': 0.8464264869689941, 'learning_rate': 9.360000000000002e-06, 'epoch': 0.0936, 'num_input_tokens_seen': 490733566, 'completed': '9.36% (117 / 1_250)', 'remaining time': '10:55:23', 'throughput': '119305.73', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:55:43,969 >> {'loss': 1.6526, 'grad_norm': 0.5264370441436768, 'learning_rate': 9.440000000000001e-06, 'epoch': 0.0944, 'num_input_tokens_seen': 494927870, 'completed': '9.44% (118 / 1_250)', 'remaining time': '10:54:55', 'throughput': '118529.19', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:56:18,439 >> {'loss': 1.7254, 'grad_norm': 0.7828117609024048, 'learning_rate': 9.52e-06, 'epoch': 0.0952, 'num_input_tokens_seen': 499122174, 'completed': '9.52% (119 / 1_250)', 'remaining time': '10:54:18', 'throughput': '121678.89', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:56:53,323 >> {'loss': 1.6528, 'grad_norm': 0.5226854085922241, 'learning_rate': 9.600000000000001e-06, 'epoch': 0.096, 'num_input_tokens_seen': 503316478, 'completed': '9.60% (120 / 1_250)', 'remaining time': '10:53:45', 'throughput': '120235.06', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:57:25,395 >> {'loss': 1.7307, 'grad_norm': 0.6121880412101746, 'learning_rate': 9.68e-06, 'epoch': 0.0968, 'num_input_tokens_seen': 507510782, 'completed': '9.68% (121 / 1_250)', 'remaining time': '10:52:45', 'throughput': '130778.50', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:58:00,966 >> {'loss': 1.7292, 'grad_norm': 0.7520681023597717, 'learning_rate': 9.760000000000001e-06, 'epoch': 0.0976, 'num_input_tokens_seen': 511705086, 'completed': '9.76% (122 / 1_250)', 'remaining time': '10:52:19', 'throughput': '117914.10', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:58:36,243 >> {'loss': 1.6413, 'grad_norm': 0.3977324962615967, 'learning_rate': 9.84e-06, 'epoch': 0.0984, 'num_input_tokens_seen': 515899390, 'completed': '9.84% (123 / 1_250)', 'remaining time': '10:51:50', 'throughput': '118894.57', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:59:07,963 >> {'loss': 1.6526, 'grad_norm': 0.7179743647575378, 'learning_rate': 9.920000000000002e-06, 'epoch': 0.0992, 'num_input_tokens_seen': 520093694, 'completed': '9.92% (124 / 1_250)', 'remaining time': '10:50:48', 'throughput': '132231.62', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 02:59:43,282 >> {'loss': 1.6211, 'grad_norm': 0.4029805064201355, 'learning_rate': 1e-05, 'epoch': 0.1, 'num_input_tokens_seen': 524287998, 'completed': '10.00% (125 / 1_250)', 'remaining time': '10:50:19', 'throughput': '118755.70', 'gpu_mem_free': '16314MB'} +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:689: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:689: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:689: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:689: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:689: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:689: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:689: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:689: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +[INFO|trainer.py:3503] 2026-05-02 02:59:51,275 >> Saving model checkpoint to /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-125 +[INFO|configuration_utils.py:472] 2026-05-02 02:59:51,277 >> Configuration saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-125/config.json +[INFO|configuration_utils.py:807] 2026-05-02 02:59:51,277 >> Configuration saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-125/generation_config.json +[INFO|modeling_utils.py:2807] 2026-05-02 03:00:03,169 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 3 checkpoint shards. You can find where each parameters has been saved in the index located at /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-125/model.safetensors.index.json. +[INFO|tokenization_utils_base.py:2684] 2026-05-02 03:00:03,171 >> tokenizer config file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-125/tokenizer_config.json +[INFO|tokenization_utils_base.py:2693] 2026-05-02 03:00:03,171 >> Special tokens file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-125/special_tokens_map.json +[INFO|tokenization_utils_base.py:2684] 2026-05-02 03:00:08,678 >> tokenizer config file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/tokenizer_config.json +[INFO|tokenization_utils_base.py:2693] 2026-05-02 03:00:08,678 >> Special tokens file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/special_tokens_map.json +05/02/2026 03:00:08 - WARNING - streaming.base.dataset - Because `num_canonical_nodes` was not specified, and `shuffle_algo` is py1e, it will default to be equal to physical nodes. Prior to Streaming v0.7.0, `num_canonical_nodes` defaulted to 64 * physical nodes. +05/02/2026 03:00:08 - WARNING - streaming.base.dataset - Because `shuffle_block_size` was not specified, it will default to max(4_000_000 // num_canonical_nodes, 1 << 18) if num_canonical_nodes is not None, otherwise 262144. Prior to Streaming v0.7.0, `shuffle_block_size` defaulted to 262144. +[WARNING|trainer.py:870] 2026-05-02 03:00:08,683 >> Save streaming dataset state: {'epoch': 0, 'sample_in_epoch': 32000, 'num_canonical_nodes': 2, 'shuffle_seed': 42, 'initial_physical_nodes': 2} +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/utils/checkpoint.py:1399: FutureWarning: `torch.cpu.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cpu', args...)` instead. + with device_autocast_ctx, torch.cpu.amp.autocast(**cpu_autocast_kwargs), recompute_context: # type: ignore[attr-defined] +[INFO|trainer.py:175] 2026-05-02 03:00:43,456 >> {'loss': 1.6946, 'grad_norm': 0.538133978843689, 'learning_rate': 9.999982454048023e-06, 'epoch': 0.1008, 'num_input_tokens_seen': 528482301, 'completed': '10.08% (126 / 1_250)', 'remaining time': '10:53:32', 'throughput': '69702.02', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:01:18,627 >> {'loss': 1.6045, 'grad_norm': 0.6322822570800781, 'learning_rate': 9.999929816328918e-06, 'epoch': 0.1016, 'num_input_tokens_seen': 532676605, 'completed': '10.16% (127 / 1_250)', 'remaining time': '10:52:59', 'throughput': '119254.23', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:01:49,770 >> {'loss': 1.6221, 'grad_norm': 0.7845800518989563, 'learning_rate': 9.999842087253164e-06, 'epoch': 0.1024, 'num_input_tokens_seen': 536870909, 'completed': '10.24% (128 / 1_250)', 'remaining time': '10:51:51', 'throughput': '134682.50', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:02:20,558 >> {'loss': 1.7763, 'grad_norm': 0.5673946142196655, 'learning_rate': 9.99971926750489e-06, 'epoch': 0.1032, 'num_input_tokens_seen': 541065213, 'completed': '10.32% (129 / 1_250)', 'remaining time': '10:50:41', 'throughput': '136230.65', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:02:54,971 >> {'loss': 1.6371, 'grad_norm': 0.45798733830451965, 'learning_rate': 9.999561358041869e-06, 'epoch': 0.104, 'num_input_tokens_seen': 545259517, 'completed': '10.40% (130 / 1_250)', 'remaining time': '10:50:03', 'throughput': '121879.09', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:03:27,199 >> {'loss': 1.6847, 'grad_norm': 0.3978565037250519, 'learning_rate': 9.999368360095512e-06, 'epoch': 0.1048, 'num_input_tokens_seen': 549453821, 'completed': '10.48% (131 / 1_250)', 'remaining time': '10:49:06', 'throughput': '130147.58', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:04:02,179 >> {'loss': 1.4595, 'grad_norm': 0.41800886392593384, 'learning_rate': 9.999140275170855e-06, 'epoch': 0.1056, 'num_input_tokens_seen': 553648125, 'completed': '10.56% (132 / 1_250)', 'remaining time': '10:48:32', 'throughput': '119906.48', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:04:37,503 >> {'loss': 1.7323, 'grad_norm': 0.4484696686267853, 'learning_rate': 9.99887710504655e-06, 'epoch': 0.1064, 'num_input_tokens_seen': 557842429, 'completed': '10.64% (133 / 1_250)', 'remaining time': '10:48:02', 'throughput': '118737.94', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:05:13,033 >> {'loss': 1.725, 'grad_norm': 0.42496952414512634, 'learning_rate': 9.99857885177485e-06, 'epoch': 0.1072, 'num_input_tokens_seen': 562036733, 'completed': '10.72% (134 / 1_250)', 'remaining time': '10:47:33', 'throughput': '118048.53', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:05:45,045 >> {'loss': 1.6291, 'grad_norm': 0.3177672326564789, 'learning_rate': 9.998245517681596e-06, 'epoch': 0.108, 'num_input_tokens_seen': 566231037, 'completed': '10.80% (135 / 1_250)', 'remaining time': '10:46:35', 'throughput': '131024.54', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:06:20,540 >> {'loss': 1.4786, 'grad_norm': 0.3028115928173065, 'learning_rate': 9.997877105366191e-06, 'epoch': 0.1088, 'num_input_tokens_seen': 570425341, 'completed': '10.88% (136 / 1_250)', 'remaining time': '10:46:06', 'throughput': '118165.81', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:06:52,276 >> {'loss': 1.8405, 'grad_norm': 0.6220481395721436, 'learning_rate': 9.99747361770159e-06, 'epoch': 0.1096, 'num_input_tokens_seen': 574619645, 'completed': '10.96% (137 / 1_250)', 'remaining time': '10:45:06', 'throughput': '132162.59', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:07:27,449 >> {'loss': 1.6506, 'grad_norm': 0.5651612877845764, 'learning_rate': 9.997035057834271e-06, 'epoch': 0.1104, 'num_input_tokens_seen': 578813949, 'completed': '11.04% (138 / 1_250)', 'remaining time': '10:44:35', 'throughput': '119247.59', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:08:02,861 >> {'loss': 1.6235, 'grad_norm': 0.3241730332374573, 'learning_rate': 9.996561429184212e-06, 'epoch': 0.1112, 'num_input_tokens_seen': 583008253, 'completed': '11.12% (139 / 1_250)', 'remaining time': '10:44:05', 'throughput': '118441.16', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:08:38,391 >> {'loss': 1.6002, 'grad_norm': 0.7132129073143005, 'learning_rate': 9.996052735444863e-06, 'epoch': 0.112, 'num_input_tokens_seen': 587202557, 'completed': '11.20% (140 / 1_250)', 'remaining time': '10:43:36', 'throughput': '118051.83', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:09:13,988 >> {'loss': 1.8347, 'grad_norm': 0.6826454401016235, 'learning_rate': 9.995508980583122e-06, 'epoch': 0.1128, 'num_input_tokens_seen': 591396861, 'completed': '11.28% (141 / 1_250)', 'remaining time': '10:43:08', 'throughput': '117824.38', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:09:49,408 >> {'loss': 1.6159, 'grad_norm': 0.29655134677886963, 'learning_rate': 9.994930168839298e-06, 'epoch': 0.1136, 'num_input_tokens_seen': 595591165, 'completed': '11.36% (142 / 1_250)', 'remaining time': '10:42:38', 'throughput': '118416.58', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:10:23,529 >> {'loss': 1.6506, 'grad_norm': 0.5438554286956787, 'learning_rate': 9.99431630472708e-06, 'epoch': 0.1144, 'num_input_tokens_seen': 599785469, 'completed': '11.44% (143 / 1_250)', 'remaining time': '10:41:58', 'throughput': '122926.86', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:10:58,745 >> {'loss': 1.6507, 'grad_norm': 0.5207958221435547, 'learning_rate': 9.993667393033505e-06, 'epoch': 0.1152, 'num_input_tokens_seen': 603979773, 'completed': '11.52% (144 / 1_250)', 'remaining time': '10:41:26', 'throughput': '119101.60', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:11:34,039 >> {'loss': 1.4801, 'grad_norm': 0.4438527524471283, 'learning_rate': 9.992983438818916e-06, 'epoch': 0.116, 'num_input_tokens_seen': 608174077, 'completed': '11.60% (145 / 1_250)', 'remaining time': '10:40:55', 'throughput': '118839.57', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:12:09,440 >> {'loss': 1.6069, 'grad_norm': 0.4111548364162445, 'learning_rate': 9.992264447416925e-06, 'epoch': 0.1168, 'num_input_tokens_seen': 612368381, 'completed': '11.68% (146 / 1_250)', 'remaining time': '10:40:25', 'throughput': '118478.40', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:12:44,970 >> {'loss': 1.6491, 'grad_norm': 0.3544377386569977, 'learning_rate': 9.991510424434373e-06, 'epoch': 0.1176, 'num_input_tokens_seen': 616562685, 'completed': '11.76% (147 / 1_250)', 'remaining time': '10:39:56', 'throughput': '118049.85', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:13:18,100 >> {'loss': 1.5581, 'grad_norm': 0.40525421500205994, 'learning_rate': 9.990721375751281e-06, 'epoch': 0.1184, 'num_input_tokens_seen': 620756989, 'completed': '11.84% (148 / 1_250)', 'remaining time': '10:39:08', 'throughput': '126601.32', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:13:50,250 >> {'loss': 1.6711, 'grad_norm': 0.5045270323753357, 'learning_rate': 9.989897307520811e-06, 'epoch': 0.1192, 'num_input_tokens_seen': 624951293, 'completed': '11.92% (149 / 1_250)', 'remaining time': '10:38:14', 'throughput': '130460.89', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:14:25,278 >> {'loss': 1.68, 'grad_norm': 0.2699918746948242, 'learning_rate': 9.98903822616921e-06, 'epoch': 0.12, 'num_input_tokens_seen': 629145597, 'completed': '12.00% (150 / 1_250)', 'remaining time': '10:37:41', 'throughput': '119742.40', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:15:00,102 >> {'loss': 1.6829, 'grad_norm': 0.27247604727745056, 'learning_rate': 9.988144138395768e-06, 'epoch': 0.1208, 'num_input_tokens_seen': 633339901, 'completed': '12.08% (151 / 1_250)', 'remaining time': '10:37:06', 'throughput': '120441.91', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:15:35,415 >> {'loss': 1.805, 'grad_norm': 0.8774641156196594, 'learning_rate': 9.987215051172763e-06, 'epoch': 0.1216, 'num_input_tokens_seen': 637534205, 'completed': '12.16% (152 / 1_250)', 'remaining time': '10:36:36', 'throughput': '118773.98', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:16:07,190 >> {'loss': 1.6489, 'grad_norm': 0.4532334506511688, 'learning_rate': 9.986250971745402e-06, 'epoch': 0.1224, 'num_input_tokens_seen': 641728509, 'completed': '12.24% (153 / 1_250)', 'remaining time': '10:35:39', 'throughput': '132000.88', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:16:41,686 >> {'loss': 1.6378, 'grad_norm': 0.5126150250434875, 'learning_rate': 9.985251907631771e-06, 'epoch': 0.1232, 'num_input_tokens_seen': 645922813, 'completed': '12.32% (154 / 1_250)', 'remaining time': '10:35:02', 'throughput': '121589.37', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:17:13,631 >> {'loss': 1.6919, 'grad_norm': 0.3984348177909851, 'learning_rate': 9.984217866622771e-06, 'epoch': 0.124, 'num_input_tokens_seen': 650117117, 'completed': '12.40% (155 / 1_250)', 'remaining time': '10:34:08', 'throughput': '131297.15', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:17:45,226 >> {'loss': 1.6395, 'grad_norm': 0.9117289185523987, 'learning_rate': 9.983148856782062e-06, 'epoch': 0.1248, 'num_input_tokens_seen': 654311421, 'completed': '12.48% (156 / 1_250)', 'remaining time': '10:33:11', 'throughput': '132753.32', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:18:19,122 >> {'loss': 1.8577, 'grad_norm': 0.8659313917160034, 'learning_rate': 9.982044886445999e-06, 'epoch': 0.1256, 'num_input_tokens_seen': 658505725, 'completed': '12.56% (157 / 1_250)', 'remaining time': '10:32:30', 'throughput': '123738.88', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:18:54,367 >> {'loss': 1.7775, 'grad_norm': 0.592921793460846, 'learning_rate': 9.980905964223562e-06, 'epoch': 0.1264, 'num_input_tokens_seen': 662700029, 'completed': '12.64% (158 / 1_250)', 'remaining time': '10:31:59', 'throughput': '119005.70', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:19:29,363 >> {'loss': 1.6652, 'grad_norm': 1.021989345550537, 'learning_rate': 9.979732098996296e-06, 'epoch': 0.1272, 'num_input_tokens_seen': 666894333, 'completed': '12.72% (159 / 1_250)', 'remaining time': '10:31:26', 'throughput': '119849.50', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:20:00,832 >> {'loss': 1.6536, 'grad_norm': 0.4250953495502472, 'learning_rate': 9.97852329991824e-06, 'epoch': 0.128, 'num_input_tokens_seen': 671088637, 'completed': '12.80% (160 / 1_250)', 'remaining time': '10:30:30', 'throughput': '133285.69', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:20:36,228 >> {'loss': 1.5707, 'grad_norm': 0.8759260773658752, 'learning_rate': 9.977279576415852e-06, 'epoch': 0.1288, 'num_input_tokens_seen': 675282941, 'completed': '12.88% (161 / 1_250)', 'remaining time': '10:29:59', 'throughput': '118493.81', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:21:11,609 >> {'loss': 1.6258, 'grad_norm': 0.3863901197910309, 'learning_rate': 9.976000938187935e-06, 'epoch': 0.1296, 'num_input_tokens_seen': 679477245, 'completed': '12.96% (162 / 1_250)', 'remaining time': '10:29:29', 'throughput': '118549.23', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:21:47,216 >> {'loss': 1.6835, 'grad_norm': 0.8051341772079468, 'learning_rate': 9.974687395205567e-06, 'epoch': 0.1304, 'num_input_tokens_seen': 683671549, 'completed': '13.04% (163 / 1_250)', 'remaining time': '10:29:00', 'throughput': '117793.75', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:22:18,392 >> {'loss': 1.7956, 'grad_norm': 0.42203912138938904, 'learning_rate': 9.973338957712022e-06, 'epoch': 0.1312, 'num_input_tokens_seen': 687865853, 'completed': '13.12% (164 / 1_250)', 'remaining time': '10:28:02', 'throughput': '134533.76', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:22:53,650 >> {'loss': 1.5749, 'grad_norm': 0.6142174601554871, 'learning_rate': 9.971955636222685e-06, 'epoch': 0.132, 'num_input_tokens_seen': 692060157, 'completed': '13.20% (165 / 1_250)', 'remaining time': '10:27:31', 'throughput': '118963.17', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:23:29,110 >> {'loss': 1.7149, 'grad_norm': 0.5044836401939392, 'learning_rate': 9.970537441524975e-06, 'epoch': 0.1328, 'num_input_tokens_seen': 696254461, 'completed': '13.28% (166 / 1_250)', 'remaining time': '10:27:02', 'throughput': '118282.17', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:24:04,478 >> {'loss': 1.6916, 'grad_norm': 0.7555297017097473, 'learning_rate': 9.96908438467826e-06, 'epoch': 0.1336, 'num_input_tokens_seen': 700448765, 'completed': '13.36% (167 / 1_250)', 'remaining time': '10:26:31', 'throughput': '118588.58', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:24:36,490 >> {'loss': 1.6067, 'grad_norm': 0.5534828901290894, 'learning_rate': 9.967596477013768e-06, 'epoch': 0.1344, 'num_input_tokens_seen': 704643069, 'completed': '13.44% (168 / 1_250)', 'remaining time': '10:25:39', 'throughput': '131023.76', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:25:12,256 >> {'loss': 1.6797, 'grad_norm': 0.577589750289917, 'learning_rate': 9.966073730134503e-06, 'epoch': 0.1352, 'num_input_tokens_seen': 708837373, 'completed': '13.52% (169 / 1_250)', 'remaining time': '10:25:11', 'throughput': '117270.68', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:25:46,850 >> {'loss': 1.593, 'grad_norm': 0.3997510075569153, 'learning_rate': 9.964516155915152e-06, 'epoch': 0.136, 'num_input_tokens_seen': 713031677, 'completed': '13.60% (170 / 1_250)', 'remaining time': '10:24:36', 'throughput': '121242.21', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:26:22,236 >> {'loss': 1.7234, 'grad_norm': 0.7357490658760071, 'learning_rate': 9.962923766501988e-06, 'epoch': 0.1368, 'num_input_tokens_seen': 717225981, 'completed': '13.68% (171 / 1_250)', 'remaining time': '10:24:05', 'throughput': '118531.41', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:26:57,722 >> {'loss': 1.7896, 'grad_norm': 0.5620606541633606, 'learning_rate': 9.961296574312787e-06, 'epoch': 0.1376, 'num_input_tokens_seen': 721420285, 'completed': '13.76% (172 / 1_250)', 'remaining time': '10:23:36', 'throughput': '118197.38', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:27:31,861 >> {'loss': 1.5402, 'grad_norm': 0.7140392065048218, 'learning_rate': 9.959634592036718e-06, 'epoch': 0.1384, 'num_input_tokens_seen': 725614589, 'completed': '13.84% (173 / 1_250)', 'remaining time': '10:22:57', 'throughput': '122856.74', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:28:07,222 >> {'loss': 1.4732, 'grad_norm': 0.2655532956123352, 'learning_rate': 9.957937832634254e-06, 'epoch': 0.1392, 'num_input_tokens_seen': 729808893, 'completed': '13.92% (174 / 1_250)', 'remaining time': '10:22:27', 'throughput': '118616.08', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:28:42,704 >> {'loss': 1.8506, 'grad_norm': 0.9752252697944641, 'learning_rate': 9.956206309337067e-06, 'epoch': 0.14, 'num_input_tokens_seen': 734003197, 'completed': '14.00% (175 / 1_250)', 'remaining time': '10:21:57', 'throughput': '118208.70', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:29:18,063 >> {'loss': 1.7006, 'grad_norm': 0.56749427318573, 'learning_rate': 9.954440035647922e-06, 'epoch': 0.1408, 'num_input_tokens_seen': 738197501, 'completed': '14.08% (176 / 1_250)', 'remaining time': '10:21:26', 'throughput': '118619.02', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:29:53,336 >> {'loss': 1.7202, 'grad_norm': 0.9948061108589172, 'learning_rate': 9.952639025340575e-06, 'epoch': 0.1416, 'num_input_tokens_seen': 742391805, 'completed': '14.16% (177 / 1_250)', 'remaining time': '10:20:55', 'throughput': '118909.87', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:30:27,669 >> {'loss': 1.5481, 'grad_norm': 0.2869523763656616, 'learning_rate': 9.950803292459668e-06, 'epoch': 0.1424, 'num_input_tokens_seen': 746586109, 'completed': '14.24% (178 / 1_250)', 'remaining time': '10:20:18', 'throughput': '122165.10', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:31:01,670 >> {'loss': 1.7623, 'grad_norm': 1.0892795324325562, 'learning_rate': 9.948932851320614e-06, 'epoch': 0.1432, 'num_input_tokens_seen': 750780413, 'completed': '14.32% (179 / 1_250)', 'remaining time': '10:19:39', 'throughput': '123361.41', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:31:37,085 >> {'loss': 1.6397, 'grad_norm': 0.30252569913864136, 'learning_rate': 9.947027716509489e-06, 'epoch': 0.144, 'num_input_tokens_seen': 754974717, 'completed': '14.40% (180 / 1_250)', 'remaining time': '10:19:08', 'throughput': '118430.47', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:32:12,559 >> {'loss': 1.6305, 'grad_norm': 0.7244664430618286, 'learning_rate': 9.945087902882917e-06, 'epoch': 0.1448, 'num_input_tokens_seen': 759169021, 'completed': '14.48% (181 / 1_250)', 'remaining time': '10:18:38', 'throughput': '118238.18', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:32:47,620 >> {'loss': 1.6996, 'grad_norm': 0.4866405427455902, 'learning_rate': 9.943113425567952e-06, 'epoch': 0.1456, 'num_input_tokens_seen': 763363325, 'completed': '14.56% (182 / 1_250)', 'remaining time': '10:18:05', 'throughput': '119626.21', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:33:22,964 >> {'loss': 1.6247, 'grad_norm': 0.7961801886558533, 'learning_rate': 9.94110429996197e-06, 'epoch': 0.1464, 'num_input_tokens_seen': 767557629, 'completed': '14.64% (183 / 1_250)', 'remaining time': '10:17:34', 'throughput': '118672.37', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:33:58,143 >> {'loss': 1.5164, 'grad_norm': 0.49415114521980286, 'learning_rate': 9.93906054173253e-06, 'epoch': 0.1472, 'num_input_tokens_seen': 771751933, 'completed': '14.72% (184 / 1_250)', 'remaining time': '10:17:02', 'throughput': '119228.89', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:34:33,579 >> {'loss': 1.5699, 'grad_norm': 0.2637489438056946, 'learning_rate': 9.936982166817273e-06, 'epoch': 0.148, 'num_input_tokens_seen': 775946237, 'completed': '14.80% (185 / 1_250)', 'remaining time': '10:16:31', 'throughput': '118362.62', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:35:09,145 >> {'loss': 1.6805, 'grad_norm': 71.88530731201172, 'learning_rate': 9.934869191423783e-06, 'epoch': 0.1488, 'num_input_tokens_seen': 780140541, 'completed': '14.88% (186 / 1_250)', 'remaining time': '10:16:01', 'throughput': '117928.31', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:35:42,946 >> {'loss': 1.9142, 'grad_norm': 1.144092321395874, 'learning_rate': 9.932721632029468e-06, 'epoch': 0.1496, 'num_input_tokens_seen': 784334845, 'completed': '14.96% (187 / 1_250)', 'remaining time': '10:15:21', 'throughput': '124088.90', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:36:18,125 >> {'loss': 1.6085, 'grad_norm': 0.37000951170921326, 'learning_rate': 9.930539505381426e-06, 'epoch': 0.1504, 'num_input_tokens_seen': 788529149, 'completed': '15.04% (188 / 1_250)', 'remaining time': '10:14:49', 'throughput': '119226.32', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:36:53,176 >> {'loss': 1.5958, 'grad_norm': 0.8059859871864319, 'learning_rate': 9.928322828496319e-06, 'epoch': 0.1512, 'num_input_tokens_seen': 792723453, 'completed': '15.12% (189 / 1_250)', 'remaining time': '10:14:16', 'throughput': '119662.66', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:37:28,736 >> {'loss': 1.52, 'grad_norm': 0.45525434613227844, 'learning_rate': 9.926071618660238e-06, 'epoch': 0.152, 'num_input_tokens_seen': 796917757, 'completed': '15.20% (190 / 1_250)', 'remaining time': '10:13:46', 'throughput': '117952.33', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:38:02,810 >> {'loss': 1.6946, 'grad_norm': 0.9326852560043335, 'learning_rate': 9.923785893428571e-06, 'epoch': 0.1528, 'num_input_tokens_seen': 801112061, 'completed': '15.28% (191 / 1_250)', 'remaining time': '10:13:07', 'throughput': '123091.76', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:38:38,213 >> {'loss': 1.4533, 'grad_norm': 0.5331999063491821, 'learning_rate': 9.92146567062586e-06, 'epoch': 0.1536, 'num_input_tokens_seen': 805306365, 'completed': '15.36% (192 / 1_250)', 'remaining time': '10:12:36', 'throughput': '118472.91', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:39:13,440 >> {'loss': 1.664, 'grad_norm': 0.8165414333343506, 'learning_rate': 9.919110968345674e-06, 'epoch': 0.1544, 'num_input_tokens_seen': 809500669, 'completed': '15.44% (193 / 1_250)', 'remaining time': '10:12:04', 'throughput': '119065.16', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:39:45,214 >> {'loss': 1.7551, 'grad_norm': 0.5670603513717651, 'learning_rate': 9.916721804950448e-06, 'epoch': 0.1552, 'num_input_tokens_seen': 813694973, 'completed': '15.52% (194 / 1_250)', 'remaining time': '10:11:13', 'throughput': '132006.26', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:40:20,515 >> {'loss': 1.5931, 'grad_norm': 0.5674936771392822, 'learning_rate': 9.914298199071363e-06, 'epoch': 0.156, 'num_input_tokens_seen': 817889277, 'completed': '15.60% (195 / 1_250)', 'remaining time': '10:10:42', 'throughput': '118815.76', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:40:55,654 >> {'loss': 1.6722, 'grad_norm': 1.43386709690094, 'learning_rate': 9.911840169608182e-06, 'epoch': 0.1568, 'num_input_tokens_seen': 822083581, 'completed': '15.68% (196 / 1_250)', 'remaining time': '10:10:09', 'throughput': '119361.44', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:41:31,019 >> {'loss': 1.745, 'grad_norm': 0.4168951213359833, 'learning_rate': 9.909347735729112e-06, 'epoch': 0.1576, 'num_input_tokens_seen': 826277885, 'completed': '15.76% (197 / 1_250)', 'remaining time': '10:09:38', 'throughput': '118602.42', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:42:06,051 >> {'loss': 1.5466, 'grad_norm': 0.39093706011772156, 'learning_rate': 9.906820916870654e-06, 'epoch': 0.1584, 'num_input_tokens_seen': 830472189, 'completed': '15.84% (198 / 1_250)', 'remaining time': '10:09:05', 'throughput': '119728.46', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:42:36,892 >> {'loss': 1.8632, 'grad_norm': 0.2988360524177551, 'learning_rate': 9.904259732737449e-06, 'epoch': 0.1592, 'num_input_tokens_seen': 834666493, 'completed': '15.92% (199 / 1_250)', 'remaining time': '10:08:09', 'throughput': '135994.24', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:43:08,615 >> {'loss': 1.5743, 'grad_norm': 0.4487788677215576, 'learning_rate': 9.901664203302126e-06, 'epoch': 0.16, 'num_input_tokens_seen': 838860797, 'completed': '16.00% (200 / 1_250)', 'remaining time': '10:07:19', 'throughput': '132219.26', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:43:42,612 >> {'loss': 1.7898, 'grad_norm': 0.5630814433097839, 'learning_rate': 9.899034348805145e-06, 'epoch': 0.1608, 'num_input_tokens_seen': 843055101, 'completed': '16.08% (201 / 1_250)', 'remaining time': '10:06:40', 'throughput': '123370.90', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:44:13,709 >> {'loss': 1.7494, 'grad_norm': 0.355682909488678, 'learning_rate': 9.896370189754637e-06, 'epoch': 0.1616, 'num_input_tokens_seen': 847249405, 'completed': '16.16% (202 / 1_250)', 'remaining time': '10:05:47', 'throughput': '134880.93', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:44:49,116 >> {'loss': 1.7729, 'grad_norm': 0.5413380861282349, 'learning_rate': 9.893671746926254e-06, 'epoch': 0.1624, 'num_input_tokens_seen': 851443709, 'completed': '16.24% (203 / 1_250)', 'remaining time': '10:05:16', 'throughput': '118456.69', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:45:20,435 >> {'loss': 1.6953, 'grad_norm': 0.4028733968734741, 'learning_rate': 9.890939041362991e-06, 'epoch': 0.1632, 'num_input_tokens_seen': 855638013, 'completed': '16.32% (204 / 1_250)', 'remaining time': '10:04:24', 'throughput': '133923.07', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:45:52,444 >> {'loss': 1.696, 'grad_norm': 0.7031953930854797, 'learning_rate': 9.888172094375035e-06, 'epoch': 0.164, 'num_input_tokens_seen': 859832317, 'completed': '16.40% (205 / 1_250)', 'remaining time': '10:03:36', 'throughput': '131037.74', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:46:27,887 >> {'loss': 1.5974, 'grad_norm': 0.6902278065681458, 'learning_rate': 9.885370927539598e-06, 'epoch': 0.1648, 'num_input_tokens_seen': 864026621, 'completed': '16.48% (206 / 1_250)', 'remaining time': '10:03:05', 'throughput': '118339.42', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:46:59,932 >> {'loss': 1.6581, 'grad_norm': 0.48977580666542053, 'learning_rate': 9.88253556270074e-06, 'epoch': 0.1656, 'num_input_tokens_seen': 868220925, 'completed': '16.56% (207 / 1_250)', 'remaining time': '10:02:17', 'throughput': '130884.89', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:47:35,353 >> {'loss': 1.535, 'grad_norm': 0.6196672916412354, 'learning_rate': 9.879666021969204e-06, 'epoch': 0.1664, 'num_input_tokens_seen': 872415229, 'completed': '16.64% (208 / 1_250)', 'remaining time': '10:01:47', 'throughput': '118412.61', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:48:10,610 >> {'loss': 1.8803, 'grad_norm': 0.432487815618515, 'learning_rate': 9.876762327722247e-06, 'epoch': 0.1672, 'num_input_tokens_seen': 876609533, 'completed': '16.72% (209 / 1_250)', 'remaining time': '10:01:15', 'throughput': '118963.77', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:48:45,456 >> {'loss': 1.634, 'grad_norm': 0.746185302734375, 'learning_rate': 9.87382450260346e-06, 'epoch': 0.168, 'num_input_tokens_seen': 880803837, 'completed': '16.80% (210 / 1_250)', 'remaining time': '10:00:41', 'throughput': '120369.61', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:49:20,645 >> {'loss': 1.5717, 'grad_norm': 0.33443328738212585, 'learning_rate': 9.870852569522591e-06, 'epoch': 0.1688, 'num_input_tokens_seen': 884998141, 'completed': '16.88% (211 / 1_250)', 'remaining time': '10:00:09', 'throughput': '119190.73', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:49:56,014 >> {'loss': 1.6152, 'grad_norm': 0.44090136885643005, 'learning_rate': 9.867846551655374e-06, 'epoch': 0.1696, 'num_input_tokens_seen': 889192445, 'completed': '16.96% (212 / 1_250)', 'remaining time': '9:59:38', 'throughput': '118588.23', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:50:31,406 >> {'loss': 1.5893, 'grad_norm': 0.7613029479980469, 'learning_rate': 9.864806472443338e-06, 'epoch': 0.1704, 'num_input_tokens_seen': 893386749, 'completed': '17.04% (213 / 1_250)', 'remaining time': '9:59:07', 'throughput': '118511.78', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:51:05,327 >> {'loss': 1.6605, 'grad_norm': 0.6096315383911133, 'learning_rate': 9.861732355593633e-06, 'epoch': 0.1712, 'num_input_tokens_seen': 897581053, 'completed': '17.12% (214 / 1_250)', 'remaining time': '9:58:29', 'throughput': '123647.98', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:51:40,745 >> {'loss': 1.6202, 'grad_norm': 1.0029077529907227, 'learning_rate': 9.858624225078841e-06, 'epoch': 0.172, 'num_input_tokens_seen': 901775357, 'completed': '17.20% (215 / 1_250)', 'remaining time': '9:57:58', 'throughput': '118422.98', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:52:16,142 >> {'loss': 1.4915, 'grad_norm': 0.5092255473136902, 'learning_rate': 9.855482105136784e-06, 'epoch': 0.1728, 'num_input_tokens_seen': 905969661, 'completed': '17.28% (216 / 1_250)', 'remaining time': '9:57:26', 'throughput': '118492.06', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:52:51,379 >> {'loss': 1.3727, 'grad_norm': 0.8846010565757751, 'learning_rate': 9.852306020270349e-06, 'epoch': 0.1736, 'num_input_tokens_seen': 910163965, 'completed': '17.36% (217 / 1_250)', 'remaining time': '9:56:54', 'throughput': '119032.34', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:53:25,367 >> {'loss': 1.4621, 'grad_norm': 0.4868163466453552, 'learning_rate': 9.84909599524728e-06, 'epoch': 0.1744, 'num_input_tokens_seen': 914358269, 'completed': '17.44% (218 / 1_250)', 'remaining time': '9:56:17', 'throughput': '123406.04', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:54:00,577 >> {'loss': 1.4775, 'grad_norm': 0.7557733654975891, 'learning_rate': 9.845852055099998e-06, 'epoch': 0.1752, 'num_input_tokens_seen': 918552573, 'completed': '17.52% (219 / 1_250)', 'remaining time': '9:55:44', 'throughput': '119122.65', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:54:36,026 >> {'loss': 1.4965, 'grad_norm': 0.21558931469917297, 'learning_rate': 9.842574225125401e-06, 'epoch': 0.176, 'num_input_tokens_seen': 922746877, 'completed': '17.60% (220 / 1_250)', 'remaining time': '9:55:13', 'throughput': '118317.48', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:55:07,049 >> {'loss': 1.771, 'grad_norm': 0.8635814189910889, 'learning_rate': 9.839262530884666e-06, 'epoch': 0.1768, 'num_input_tokens_seen': 926941181, 'completed': '17.68% (221 / 1_250)', 'remaining time': '9:54:22', 'throughput': '135201.36', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:55:42,238 >> {'loss': 1.6093, 'grad_norm': 0.3397902846336365, 'learning_rate': 9.83591699820305e-06, 'epoch': 0.1776, 'num_input_tokens_seen': 931135485, 'completed': '17.76% (222 / 1_250)', 'remaining time': '9:53:50', 'throughput': '119192.67', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:56:17,448 >> {'loss': 1.716, 'grad_norm': 0.6826940774917603, 'learning_rate': 9.832537653169687e-06, 'epoch': 0.1784, 'num_input_tokens_seen': 935329789, 'completed': '17.84% (223 / 1_250)', 'remaining time': '9:53:17', 'throughput': '119122.95', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:56:52,647 >> {'loss': 1.6696, 'grad_norm': 0.316874623298645, 'learning_rate': 9.829124522137386e-06, 'epoch': 0.1792, 'num_input_tokens_seen': 939524093, 'completed': '17.92% (224 / 1_250)', 'remaining time': '9:52:45', 'throughput': '119158.40', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:57:27,879 >> {'loss': 1.7586, 'grad_norm': 0.7268978953361511, 'learning_rate': 9.825677631722436e-06, 'epoch': 0.18, 'num_input_tokens_seen': 943718397, 'completed': '18.00% (225 / 1_250)', 'remaining time': '9:52:13', 'throughput': '119048.08', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:58:02,622 >> {'loss': 1.7708, 'grad_norm': 0.4566599428653717, 'learning_rate': 9.822197008804375e-06, 'epoch': 0.1808, 'num_input_tokens_seen': 947912700, 'completed': '18.08% (226 / 1_250)', 'remaining time': '9:51:39', 'throughput': '120725.24', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:58:34,152 >> {'loss': 1.5909, 'grad_norm': 0.5628994703292847, 'learning_rate': 9.818682680525801e-06, 'epoch': 0.1816, 'num_input_tokens_seen': 952107004, 'completed': '18.16% (227 / 1_250)', 'remaining time': '9:50:50', 'throughput': '133026.34', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:59:09,556 >> {'loss': 1.4777, 'grad_norm': 0.2773268520832062, 'learning_rate': 9.815134674292151e-06, 'epoch': 0.1824, 'num_input_tokens_seen': 956301308, 'completed': '18.24% (228 / 1_250)', 'remaining time': '9:50:19', 'throughput': '118468.75', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 03:59:44,201 >> {'loss': 1.5139, 'grad_norm': 0.667258620262146, 'learning_rate': 9.811553017771494e-06, 'epoch': 0.1832, 'num_input_tokens_seen': 960495612, 'completed': '18.32% (229 / 1_250)', 'remaining time': '9:49:44', 'throughput': '121066.35', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:00:19,525 >> {'loss': 1.782, 'grad_norm': 0.25041618943214417, 'learning_rate': 9.807937738894303e-06, 'epoch': 0.184, 'num_input_tokens_seen': 964689916, 'completed': '18.40% (230 / 1_250)', 'remaining time': '9:49:12', 'throughput': '118738.70', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:00:54,860 >> {'loss': 1.5777, 'grad_norm': 0.4750188887119293, 'learning_rate': 9.804288865853251e-06, 'epoch': 0.1848, 'num_input_tokens_seen': 968884220, 'completed': '18.48% (231 / 1_250)', 'remaining time': '9:48:41', 'throughput': '118698.40', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:01:30,279 >> {'loss': 1.6811, 'grad_norm': 0.3971080780029297, 'learning_rate': 9.800606427102983e-06, 'epoch': 0.1856, 'num_input_tokens_seen': 973078524, 'completed': '18.56% (232 / 1_250)', 'remaining time': '9:48:09', 'throughput': '118420.23', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:02:05,622 >> {'loss': 1.8408, 'grad_norm': 0.6963155269622803, 'learning_rate': 9.796890451359895e-06, 'epoch': 0.1864, 'num_input_tokens_seen': 977272828, 'completed': '18.64% (233 / 1_250)', 'remaining time': '9:47:38', 'throughput': '118674.26', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:02:40,801 >> {'loss': 1.7041, 'grad_norm': 0.39788714051246643, 'learning_rate': 9.793140967601911e-06, 'epoch': 0.1872, 'num_input_tokens_seen': 981467132, 'completed': '18.72% (234 / 1_250)', 'remaining time': '9:47:05', 'throughput': '119228.33', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:03:15,968 >> {'loss': 1.7154, 'grad_norm': 0.8704416751861572, 'learning_rate': 9.789358005068262e-06, 'epoch': 0.188, 'num_input_tokens_seen': 985661436, 'completed': '18.80% (235 / 1_250)', 'remaining time': '9:46:33', 'throughput': '119267.04', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:03:47,606 >> {'loss': 1.6163, 'grad_norm': 0.7911041975021362, 'learning_rate': 9.785541593259247e-06, 'epoch': 0.1888, 'num_input_tokens_seen': 989855740, 'completed': '18.88% (236 / 1_250)', 'remaining time': '9:45:45', 'throughput': '132574.85', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:04:23,092 >> {'loss': 1.6487, 'grad_norm': 0.35582974553108215, 'learning_rate': 9.781691761936015e-06, 'epoch': 0.1896, 'num_input_tokens_seen': 994050044, 'completed': '18.96% (237 / 1_250)', 'remaining time': '9:45:14', 'throughput': '118195.42', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:04:58,250 >> {'loss': 1.521, 'grad_norm': 0.29482415318489075, 'learning_rate': 9.77780854112032e-06, 'epoch': 0.1904, 'num_input_tokens_seen': 998244348, 'completed': '19.04% (238 / 1_250)', 'remaining time': '9:44:41', 'throughput': '119297.64', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:05:33,669 >> {'loss': 1.6121, 'grad_norm': 0.3954414129257202, 'learning_rate': 9.773891961094302e-06, 'epoch': 0.1912, 'num_input_tokens_seen': 1002438652, 'completed': '19.12% (239 / 1_250)', 'remaining time': '9:44:10', 'throughput': '118420.40', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:06:09,022 >> {'loss': 1.6268, 'grad_norm': 0.4605117440223694, 'learning_rate': 9.769942052400236e-06, 'epoch': 0.192, 'num_input_tokens_seen': 1006632956, 'completed': '19.20% (240 / 1_250)', 'remaining time': '9:43:38', 'throughput': '118640.69', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:06:44,210 >> {'loss': 1.8389, 'grad_norm': 0.4178961217403412, 'learning_rate': 9.765958845840302e-06, 'epoch': 0.1928, 'num_input_tokens_seen': 1010827260, 'completed': '19.28% (241 / 1_250)', 'remaining time': '9:43:05', 'throughput': '119197.06', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:07:19,467 >> {'loss': 1.5987, 'grad_norm': 0.38006705045700073, 'learning_rate': 9.76194237247635e-06, 'epoch': 0.1936, 'num_input_tokens_seen': 1015021564, 'completed': '19.36% (242 / 1_250)', 'remaining time': '9:42:33', 'throughput': '118961.82', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:07:54,820 >> {'loss': 1.7745, 'grad_norm': 0.354481965303421, 'learning_rate': 9.757892663629641e-06, 'epoch': 0.1944, 'num_input_tokens_seen': 1019215868, 'completed': '19.44% (243 / 1_250)', 'remaining time': '9:42:01', 'throughput': '118641.24', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:08:30,178 >> {'loss': 1.6851, 'grad_norm': 0.29203394055366516, 'learning_rate': 9.753809750880624e-06, 'epoch': 0.1952, 'num_input_tokens_seen': 1023410172, 'completed': '19.52% (244 / 1_250)', 'remaining time': '9:41:29', 'throughput': '118624.22', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:09:04,702 >> {'loss': 1.5042, 'grad_norm': 0.3754411041736603, 'learning_rate': 9.749693666068664e-06, 'epoch': 0.196, 'num_input_tokens_seen': 1027604476, 'completed': '19.60% (245 / 1_250)', 'remaining time': '9:40:54', 'throughput': '121490.10', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:09:40,176 >> {'loss': 1.9218, 'grad_norm': 0.33530354499816895, 'learning_rate': 9.745544441291826e-06, 'epoch': 0.1968, 'num_input_tokens_seen': 1031798780, 'completed': '19.68% (246 / 1_250)', 'remaining time': '9:40:23', 'throughput': '118234.44', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:10:13,641 >> {'loss': 1.6885, 'grad_norm': 0.4312880337238312, 'learning_rate': 9.741362108906594e-06, 'epoch': 0.1976, 'num_input_tokens_seen': 1035993084, 'completed': '19.76% (247 / 1_250)', 'remaining time': '9:39:43', 'throughput': '125336.51', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:10:47,851 >> {'loss': 1.6758, 'grad_norm': 0.40092650055885315, 'learning_rate': 9.737146701527637e-06, 'epoch': 0.1984, 'num_input_tokens_seen': 1040187388, 'completed': '19.84% (248 / 1_250)', 'remaining time': '9:39:06', 'throughput': '122605.10', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:11:23,152 >> {'loss': 1.9499, 'grad_norm': 0.4131753146648407, 'learning_rate': 9.732898252027548e-06, 'epoch': 0.1992, 'num_input_tokens_seen': 1044381692, 'completed': '19.92% (249 / 1_250)', 'remaining time': '9:38:34', 'throughput': '118815.38', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:11:57,581 >> {'loss': 1.6493, 'grad_norm': 0.4166308641433716, 'learning_rate': 9.728616793536588e-06, 'epoch': 0.2, 'num_input_tokens_seen': 1048575996, 'completed': '20.00% (250 / 1_250)', 'remaining time': '9:37:59', 'throughput': '121825.17', 'gpu_mem_free': '16314MB'} +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:689: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +[INFO|trainer.py:3503] 2026-05-02 04:12:05,405 >> Saving model checkpoint to /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-250 +[INFO|configuration_utils.py:472] 2026-05-02 04:12:05,406 >> Configuration saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-250/config.json +[INFO|configuration_utils.py:807] 2026-05-02 04:12:05,406 >> Configuration saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-250/generation_config.json +[INFO|modeling_utils.py:2807] 2026-05-02 04:12:17,082 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 3 checkpoint shards. You can find where each parameters has been saved in the index located at /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-250/model.safetensors.index.json. +[INFO|tokenization_utils_base.py:2684] 2026-05-02 04:12:17,084 >> tokenizer config file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-250/tokenizer_config.json +[INFO|tokenization_utils_base.py:2693] 2026-05-02 04:12:17,084 >> Special tokens file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-250/special_tokens_map.json +[INFO|tokenization_utils_base.py:2684] 2026-05-02 04:12:25,592 >> tokenizer config file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/tokenizer_config.json +[INFO|tokenization_utils_base.py:2693] 2026-05-02 04:12:25,592 >> Special tokens file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/special_tokens_map.json +[INFO|trainer.py:3595] 2026-05-02 04:12:25,597 >> Deleting older checkpoint [/tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-125] due to args.save_total_limit +[WARNING|trainer.py:870] 2026-05-02 04:12:26,700 >> Save streaming dataset state: {'epoch': 0, 'sample_in_epoch': 64000, 'num_canonical_nodes': 2, 'shuffle_seed': 42, 'initial_physical_nodes': 2} +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/utils/checkpoint.py:1399: FutureWarning: `torch.cpu.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cpu', args...)` instead. + with device_autocast_ctx, torch.cpu.amp.autocast(**cpu_autocast_kwargs), recompute_context: # type: ignore[attr-defined] +[INFO|trainer.py:175] 2026-05-02 04:13:01,852 >> {'loss': 1.5831, 'grad_norm': 0.6261499524116516, 'learning_rate': 9.724302359442434e-06, 'epoch': 0.2008, 'num_input_tokens_seen': 1052770300, 'completed': '20.08% (251 / 1_250)', 'remaining time': '9:39:22', 'throughput': '65259.49', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:13:37,038 >> {'loss': 1.6244, 'grad_norm': 0.2699098587036133, 'learning_rate': 9.719954983389908e-06, 'epoch': 0.2016, 'num_input_tokens_seen': 1056964604, 'completed': '20.16% (252 / 1_250)', 'remaining time': '9:38:48', 'throughput': '119204.55', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:14:12,419 >> {'loss': 1.5909, 'grad_norm': 0.6131119728088379, 'learning_rate': 9.71557469928072e-06, 'epoch': 0.2024, 'num_input_tokens_seen': 1061158908, 'completed': '20.24% (253 / 1_250)', 'remaining time': '9:38:16', 'throughput': '118544.51', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:14:47,614 >> {'loss': 1.6284, 'grad_norm': 0.2693873941898346, 'learning_rate': 9.71116154127321e-06, 'epoch': 0.2032, 'num_input_tokens_seen': 1065353212, 'completed': '20.32% (254 / 1_250)', 'remaining time': '9:37:43', 'throughput': '119173.39', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:15:19,166 >> {'loss': 1.5886, 'grad_norm': 0.5293872952461243, 'learning_rate': 9.706715543782065e-06, 'epoch': 0.204, 'num_input_tokens_seen': 1069547516, 'completed': '20.40% (255 / 1_250)', 'remaining time': '9:36:55', 'throughput': '132934.80', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:15:50,770 >> {'loss': 1.659, 'grad_norm': 0.2523781657218933, 'learning_rate': 9.702236741478072e-06, 'epoch': 0.2048, 'num_input_tokens_seen': 1073741820, 'completed': '20.48% (256 / 1_250)', 'remaining time': '9:36:08', 'throughput': '132711.76', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:16:25,099 >> {'loss': 1.6138, 'grad_norm': 0.9789847731590271, 'learning_rate': 9.697725169287827e-06, 'epoch': 0.2056, 'num_input_tokens_seen': 1077936124, 'completed': '20.56% (257 / 1_250)', 'remaining time': '9:35:32', 'throughput': '122179.87', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:17:00,377 >> {'loss': 1.6522, 'grad_norm': 0.6933457851409912, 'learning_rate': 9.693180862393476e-06, 'epoch': 0.2064, 'num_input_tokens_seen': 1082130428, 'completed': '20.64% (258 / 1_250)', 'remaining time': '9:34:59', 'throughput': '118894.78', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:17:35,780 >> {'loss': 1.5504, 'grad_norm': 0.49673616886138916, 'learning_rate': 9.68860385623244e-06, 'epoch': 0.2072, 'num_input_tokens_seen': 1086324732, 'completed': '20.72% (259 / 1_250)', 'remaining time': '9:34:26', 'throughput': '118471.14', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:18:11,141 >> {'loss': 1.7199, 'grad_norm': 1.152982234954834, 'learning_rate': 9.683994186497132e-06, 'epoch': 0.208, 'num_input_tokens_seen': 1090519036, 'completed': '20.80% (260 / 1_250)', 'remaining time': '9:33:54', 'throughput': '118615.98', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:18:46,497 >> {'loss': 1.4769, 'grad_norm': 0.24013905227184296, 'learning_rate': 9.679351889134681e-06, 'epoch': 0.2088, 'num_input_tokens_seen': 1094713340, 'completed': '20.88% (261 / 1_250)', 'remaining time': '9:33:21', 'throughput': '118631.07', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:19:21,798 >> {'loss': 1.5913, 'grad_norm': 0.96748286485672, 'learning_rate': 9.674677000346654e-06, 'epoch': 0.2096, 'num_input_tokens_seen': 1098907644, 'completed': '20.96% (262 / 1_250)', 'remaining time': '9:32:48', 'throughput': '118815.44', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:19:53,730 >> {'loss': 1.5599, 'grad_norm': 0.5607587695121765, 'learning_rate': 9.669969556588776e-06, 'epoch': 0.2104, 'num_input_tokens_seen': 1103101948, 'completed': '21.04% (263 / 1_250)', 'remaining time': '9:32:03', 'throughput': '131351.17', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:20:29,169 >> {'loss': 1.5636, 'grad_norm': 0.7532386779785156, 'learning_rate': 9.665229594570635e-06, 'epoch': 0.2112, 'num_input_tokens_seen': 1107296252, 'completed': '21.12% (264 / 1_250)', 'remaining time': '9:31:31', 'throughput': '118350.56', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:21:00,989 >> {'loss': 1.6577, 'grad_norm': 0.46795937418937683, 'learning_rate': 9.66045715125541e-06, 'epoch': 0.212, 'num_input_tokens_seen': 1111490556, 'completed': '21.20% (265 / 1_250)', 'remaining time': '9:30:45', 'throughput': '131814.95', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:21:32,242 >> {'loss': 1.7128, 'grad_norm': 0.538840115070343, 'learning_rate': 9.65565226385957e-06, 'epoch': 0.2128, 'num_input_tokens_seen': 1115684860, 'completed': '21.28% (266 / 1_250)', 'remaining time': '9:29:57', 'throughput': '134203.76', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:22:07,486 >> {'loss': 1.8306, 'grad_norm': 1.170693039894104, 'learning_rate': 9.650814969852595e-06, 'epoch': 0.2136, 'num_input_tokens_seen': 1119879164, 'completed': '21.36% (267 / 1_250)', 'remaining time': '9:29:24', 'throughput': '119008.74', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:22:42,944 >> {'loss': 1.6172, 'grad_norm': 0.6258639097213745, 'learning_rate': 9.645945306956676e-06, 'epoch': 0.2144, 'num_input_tokens_seen': 1124073468, 'completed': '21.44% (268 / 1_250)', 'remaining time': '9:28:52', 'throughput': '118288.17', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:23:18,306 >> {'loss': 1.6524, 'grad_norm': 0.577654242515564, 'learning_rate': 9.641043313146418e-06, 'epoch': 0.2152, 'num_input_tokens_seen': 1128267772, 'completed': '21.52% (269 / 1_250)', 'remaining time': '9:28:19', 'throughput': '118612.17', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:23:49,815 >> {'loss': 1.6405, 'grad_norm': 0.6162702441215515, 'learning_rate': 9.636109026648556e-06, 'epoch': 0.216, 'num_input_tokens_seen': 1132462076, 'completed': '21.60% (270 / 1_250)', 'remaining time': '9:27:33', 'throughput': '133111.86', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:24:21,065 >> {'loss': 1.8092, 'grad_norm': 0.5771951079368591, 'learning_rate': 9.631142485941646e-06, 'epoch': 0.2168, 'num_input_tokens_seen': 1136656380, 'completed': '21.68% (271 / 1_250)', 'remaining time': '9:26:45', 'throughput': '134218.12', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:24:56,032 >> {'loss': 1.7491, 'grad_norm': 0.5879819393157959, 'learning_rate': 9.626143729755774e-06, 'epoch': 0.2176, 'num_input_tokens_seen': 1140850684, 'completed': '21.76% (272 / 1_250)', 'remaining time': '9:26:11', 'throughput': '119949.40', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:25:31,412 >> {'loss': 1.7243, 'grad_norm': 0.6389369368553162, 'learning_rate': 9.621112797072243e-06, 'epoch': 0.2184, 'num_input_tokens_seen': 1145044988, 'completed': '21.84% (273 / 1_250)', 'remaining time': '9:25:39', 'throughput': '118553.13', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:26:06,936 >> {'loss': 1.8609, 'grad_norm': 0.4822394549846649, 'learning_rate': 9.616049727123273e-06, 'epoch': 0.2192, 'num_input_tokens_seen': 1149239292, 'completed': '21.92% (274 / 1_250)', 'remaining time': '9:25:07', 'throughput': '118067.78', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:26:42,583 >> {'loss': 1.7405, 'grad_norm': 0.4842619299888611, 'learning_rate': 9.610954559391704e-06, 'epoch': 0.22, 'num_input_tokens_seen': 1153433596, 'completed': '22.00% (275 / 1_250)', 'remaining time': '9:24:36', 'throughput': '117662.27', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:27:17,946 >> {'loss': 1.5516, 'grad_norm': 0.42631465196609497, 'learning_rate': 9.605827333610678e-06, 'epoch': 0.2208, 'num_input_tokens_seen': 1157627900, 'completed': '22.08% (276 / 1_250)', 'remaining time': '9:24:03', 'throughput': '118608.91', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:27:53,160 >> {'loss': 1.7024, 'grad_norm': 0.43788233399391174, 'learning_rate': 9.600668089763331e-06, 'epoch': 0.2216, 'num_input_tokens_seen': 1161822204, 'completed': '22.16% (277 / 1_250)', 'remaining time': '9:23:30', 'throughput': '119108.80', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:28:28,649 >> {'loss': 1.5353, 'grad_norm': 0.32826539874076843, 'learning_rate': 9.595476868082481e-06, 'epoch': 0.2224, 'num_input_tokens_seen': 1166016507, 'completed': '22.24% (278 / 1_250)', 'remaining time': '9:22:58', 'throughput': '118184.16', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:29:03,944 >> {'loss': 1.5988, 'grad_norm': 0.32516995072364807, 'learning_rate': 9.59025370905032e-06, 'epoch': 0.2232, 'num_input_tokens_seen': 1170210811, 'completed': '22.32% (279 / 1_250)', 'remaining time': '9:22:25', 'throughput': '118834.78', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:29:39,439 >> {'loss': 1.7789, 'grad_norm': 0.8606049418449402, 'learning_rate': 9.58499865339809e-06, 'epoch': 0.224, 'num_input_tokens_seen': 1174405115, 'completed': '22.40% (280 / 1_250)', 'remaining time': '9:21:53', 'throughput': '118168.83', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:30:14,935 >> {'loss': 1.6502, 'grad_norm': 0.7322668433189392, 'learning_rate': 9.579711742105771e-06, 'epoch': 0.2248, 'num_input_tokens_seen': 1178599419, 'completed': '22.48% (281 / 1_250)', 'remaining time': '9:21:20', 'throughput': '118161.46', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:30:50,191 >> {'loss': 1.8123, 'grad_norm': 0.27003875374794006, 'learning_rate': 9.574393016401758e-06, 'epoch': 0.2256, 'num_input_tokens_seen': 1182793723, 'completed': '22.56% (282 / 1_250)', 'remaining time': '9:20:47', 'throughput': '118966.66', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:31:25,345 >> {'loss': 1.4985, 'grad_norm': 0.6241596937179565, 'learning_rate': 9.569042517762544e-06, 'epoch': 0.2264, 'num_input_tokens_seen': 1186988027, 'completed': '22.64% (283 / 1_250)', 'remaining time': '9:20:14', 'throughput': '119310.94', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:31:57,470 >> {'loss': 1.6287, 'grad_norm': 0.2969931662082672, 'learning_rate': 9.563660287912394e-06, 'epoch': 0.2272, 'num_input_tokens_seen': 1191182331, 'completed': '22.72% (284 / 1_250)', 'remaining time': '9:19:30', 'throughput': '130565.79', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:32:33,125 >> {'loss': 1.7248, 'grad_norm': 0.7072494626045227, 'learning_rate': 9.558246368823013e-06, 'epoch': 0.228, 'num_input_tokens_seen': 1195376635, 'completed': '22.80% (285 / 1_250)', 'remaining time': '9:18:59', 'throughput': '117633.11', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:33:08,581 >> {'loss': 1.6871, 'grad_norm': 0.3306654095649719, 'learning_rate': 9.552800802713232e-06, 'epoch': 0.2288, 'num_input_tokens_seen': 1199570939, 'completed': '22.88% (286 / 1_250)', 'remaining time': '9:18:26', 'throughput': '118298.38', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:33:44,015 >> {'loss': 1.8389, 'grad_norm': 0.6577323079109192, 'learning_rate': 9.54732363204867e-06, 'epoch': 0.2296, 'num_input_tokens_seen': 1203765243, 'completed': '22.96% (287 / 1_250)', 'remaining time': '9:17:54', 'throughput': '118367.12', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:34:15,117 >> {'loss': 1.6547, 'grad_norm': 0.4482329189777374, 'learning_rate': 9.541814899541403e-06, 'epoch': 0.2304, 'num_input_tokens_seen': 1207959547, 'completed': '23.04% (288 / 1_250)', 'remaining time': '9:17:07', 'throughput': '134857.74', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:34:50,602 >> {'loss': 1.5871, 'grad_norm': 0.42961087822914124, 'learning_rate': 9.536274648149636e-06, 'epoch': 0.2312, 'num_input_tokens_seen': 1212153851, 'completed': '23.12% (289 / 1_250)', 'remaining time': '9:16:34', 'throughput': '118199.05', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:35:24,619 >> {'loss': 1.6419, 'grad_norm': 0.5469327569007874, 'learning_rate': 9.530702921077358e-06, 'epoch': 0.232, 'num_input_tokens_seen': 1216348155, 'completed': '23.20% (290 / 1_250)', 'remaining time': '9:15:57', 'throughput': '123301.73', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:35:59,727 >> {'loss': 1.7127, 'grad_norm': 0.33383533358573914, 'learning_rate': 9.525099761774021e-06, 'epoch': 0.2328, 'num_input_tokens_seen': 1220542459, 'completed': '23.28% (291 / 1_250)', 'remaining time': '9:15:24', 'throughput': '119468.49', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:36:34,666 >> {'loss': 1.6106, 'grad_norm': 0.299721896648407, 'learning_rate': 9.519465213934183e-06, 'epoch': 0.2336, 'num_input_tokens_seen': 1224736763, 'completed': '23.36% (292 / 1_250)', 'remaining time': '9:14:50', 'throughput': '120044.84', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:37:10,057 >> {'loss': 1.446, 'grad_norm': 0.37808722257614136, 'learning_rate': 9.513799321497179e-06, 'epoch': 0.2344, 'num_input_tokens_seen': 1228931067, 'completed': '23.44% (293 / 1_250)', 'remaining time': '9:14:17', 'throughput': '118514.43', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:37:44,905 >> {'loss': 1.5226, 'grad_norm': 0.33474305272102356, 'learning_rate': 9.50810212864678e-06, 'epoch': 0.2352, 'num_input_tokens_seen': 1233125371, 'completed': '23.52% (294 / 1_250)', 'remaining time': '9:13:42', 'throughput': '120361.01', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:38:16,107 >> {'loss': 1.7401, 'grad_norm': 0.3066512644290924, 'learning_rate': 9.50237367981084e-06, 'epoch': 0.236, 'num_input_tokens_seen': 1237319675, 'completed': '23.60% (295 / 1_250)', 'remaining time': '9:12:56', 'throughput': '134422.24', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:38:47,453 >> {'loss': 1.7764, 'grad_norm': 0.3993739187717438, 'learning_rate': 9.49661401966095e-06, 'epoch': 0.2368, 'num_input_tokens_seen': 1241513979, 'completed': '23.68% (296 / 1_250)', 'remaining time': '9:12:11', 'throughput': '133805.18', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:39:22,888 >> {'loss': 1.6129, 'grad_norm': 0.3452647030353546, 'learning_rate': 9.490823193112103e-06, 'epoch': 0.2376, 'num_input_tokens_seen': 1245708283, 'completed': '23.76% (297 / 1_250)', 'remaining time': '9:11:38', 'throughput': '118366.90', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:39:58,269 >> {'loss': 1.7604, 'grad_norm': 0.2961893677711487, 'learning_rate': 9.485001245322321e-06, 'epoch': 0.2384, 'num_input_tokens_seen': 1249902587, 'completed': '23.84% (298 / 1_250)', 'remaining time': '9:11:05', 'throughput': '118546.14', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:40:32,557 >> {'loss': 1.4616, 'grad_norm': 0.20523588359355927, 'learning_rate': 9.479148221692327e-06, 'epoch': 0.2392, 'num_input_tokens_seen': 1254096891, 'completed': '23.92% (299 / 1_250)', 'remaining time': '9:10:29', 'throughput': '122328.33', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:41:07,556 >> {'loss': 1.7044, 'grad_norm': 0.23272308707237244, 'learning_rate': 9.473264167865172e-06, 'epoch': 0.24, 'num_input_tokens_seen': 1258291195, 'completed': '24.00% (300 / 1_250)', 'remaining time': '9:09:55', 'throughput': '119840.24', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:41:43,030 >> {'loss': 1.6683, 'grad_norm': 0.4301333427429199, 'learning_rate': 9.467349129725892e-06, 'epoch': 0.2408, 'num_input_tokens_seen': 1262485499, 'completed': '24.08% (301 / 1_250)', 'remaining time': '9:09:23', 'throughput': '118236.06', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:42:18,580 >> {'loss': 1.6566, 'grad_norm': 0.48182588815689087, 'learning_rate': 9.461403153401142e-06, 'epoch': 0.2416, 'num_input_tokens_seen': 1266679803, 'completed': '24.16% (302 / 1_250)', 'remaining time': '9:08:51', 'throughput': '117981.38', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:42:53,736 >> {'loss': 1.6632, 'grad_norm': 0.438286155462265, 'learning_rate': 9.45542628525884e-06, 'epoch': 0.2424, 'num_input_tokens_seen': 1270874107, 'completed': '24.24% (303 / 1_250)', 'remaining time': '9:08:17', 'throughput': '119305.48', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:43:29,142 >> {'loss': 1.6271, 'grad_norm': 0.4110262095928192, 'learning_rate': 9.449418571907802e-06, 'epoch': 0.2432, 'num_input_tokens_seen': 1275068411, 'completed': '24.32% (304 / 1_250)', 'remaining time': '9:07:45', 'throughput': '118465.55', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:44:03,493 >> {'loss': 1.603, 'grad_norm': 0.39661532640457153, 'learning_rate': 9.443380060197387e-06, 'epoch': 0.244, 'num_input_tokens_seen': 1279262715, 'completed': '24.40% (305 / 1_250)', 'remaining time': '9:07:09', 'throughput': '122100.06', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:44:34,141 >> {'loss': 1.6936, 'grad_norm': 0.34887561202049255, 'learning_rate': 9.437310797217121e-06, 'epoch': 0.2448, 'num_input_tokens_seen': 1283457019, 'completed': '24.48% (306 / 1_250)', 'remaining time': '9:06:21', 'throughput': '136854.62', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:45:09,463 >> {'loss': 1.5315, 'grad_norm': 0.44347426295280457, 'learning_rate': 9.431210830296336e-06, 'epoch': 0.2456, 'num_input_tokens_seen': 1287651323, 'completed': '24.56% (307 / 1_250)', 'remaining time': '9:05:49', 'throughput': '118744.08', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:45:43,598 >> {'loss': 1.7153, 'grad_norm': 0.5454867482185364, 'learning_rate': 9.425080207003798e-06, 'epoch': 0.2464, 'num_input_tokens_seen': 1291845627, 'completed': '24.64% (308 / 1_250)', 'remaining time': '9:05:12', 'throughput': '122874.42', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:46:14,482 >> {'loss': 1.5902, 'grad_norm': 0.7534891366958618, 'learning_rate': 9.41891897514734e-06, 'epoch': 0.2472, 'num_input_tokens_seen': 1296039931, 'completed': '24.72% (309 / 1_250)', 'remaining time': '9:04:26', 'throughput': '135809.49', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:46:50,079 >> {'loss': 1.6723, 'grad_norm': 0.35564130544662476, 'learning_rate': 9.412727182773487e-06, 'epoch': 0.248, 'num_input_tokens_seen': 1300234235, 'completed': '24.80% (310 / 1_250)', 'remaining time': '9:03:53', 'throughput': '117826.59', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:47:25,207 >> {'loss': 1.5847, 'grad_norm': 0.9316515922546387, 'learning_rate': 9.406504878167078e-06, 'epoch': 0.2488, 'num_input_tokens_seen': 1304428539, 'completed': '24.88% (311 / 1_250)', 'remaining time': '9:03:20', 'throughput': '119400.36', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:48:00,562 >> {'loss': 1.7187, 'grad_norm': 0.2831796109676361, 'learning_rate': 9.400252109850894e-06, 'epoch': 0.2496, 'num_input_tokens_seen': 1308622843, 'completed': '24.96% (312 / 1_250)', 'remaining time': '9:02:47', 'throughput': '118632.78', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:48:32,086 >> {'loss': 1.7057, 'grad_norm': 1.5329827070236206, 'learning_rate': 9.393968926585281e-06, 'epoch': 0.2504, 'num_input_tokens_seen': 1312817147, 'completed': '25.04% (313 / 1_250)', 'remaining time': '9:02:03', 'throughput': '133052.37', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:49:04,122 >> {'loss': 1.5903, 'grad_norm': 0.37552690505981445, 'learning_rate': 9.387655377367759e-06, 'epoch': 0.2512, 'num_input_tokens_seen': 1317011451, 'completed': '25.12% (314 / 1_250)', 'remaining time': '9:01:20', 'throughput': '130924.93', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:49:38,699 >> {'loss': 1.3737, 'grad_norm': 0.7426468729972839, 'learning_rate': 9.381311511432659e-06, 'epoch': 0.252, 'num_input_tokens_seen': 1321205755, 'completed': '25.20% (315 / 1_250)', 'remaining time': '9:00:45', 'throughput': '121302.42', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:50:13,773 >> {'loss': 1.6792, 'grad_norm': 0.278263121843338, 'learning_rate': 9.37493737825072e-06, 'epoch': 0.2528, 'num_input_tokens_seen': 1325400059, 'completed': '25.28% (316 / 1_250)', 'remaining time': '9:00:12', 'throughput': '119586.30', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:50:48,872 >> {'loss': 1.6944, 'grad_norm': 0.5596902966499329, 'learning_rate': 9.36853302752871e-06, 'epoch': 0.2536, 'num_input_tokens_seen': 1329594363, 'completed': '25.36% (317 / 1_250)', 'remaining time': '8:59:38', 'throughput': '119498.81', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:51:20,377 >> {'loss': 1.6469, 'grad_norm': 0.27727746963500977, 'learning_rate': 9.362098509209046e-06, 'epoch': 0.2544, 'num_input_tokens_seen': 1333788667, 'completed': '25.44% (318 / 1_250)', 'remaining time': '8:58:54', 'throughput': '133131.26', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:51:55,514 >> {'loss': 1.703, 'grad_norm': 0.739952802658081, 'learning_rate': 9.355633873469394e-06, 'epoch': 0.2552, 'num_input_tokens_seen': 1337982971, 'completed': '25.52% (319 / 1_250)', 'remaining time': '8:58:21', 'throughput': '119368.83', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:52:30,908 >> {'loss': 1.629, 'grad_norm': 0.3802284598350525, 'learning_rate': 9.34913917072228e-06, 'epoch': 0.256, 'num_input_tokens_seen': 1342177275, 'completed': '25.60% (320 / 1_250)', 'remaining time': '8:57:48', 'throughput': '118503.16', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:53:06,442 >> {'loss': 1.491, 'grad_norm': 0.8854534029960632, 'learning_rate': 9.342614451614704e-06, 'epoch': 0.2568, 'num_input_tokens_seen': 1346371579, 'completed': '25.68% (321 / 1_250)', 'remaining time': '8:57:16', 'throughput': '118037.81', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:53:41,726 >> {'loss': 1.5728, 'grad_norm': 0.33788129687309265, 'learning_rate': 9.336059767027732e-06, 'epoch': 0.2576, 'num_input_tokens_seen': 1350565883, 'completed': '25.76% (322 / 1_250)', 'remaining time': '8:56:43', 'throughput': '118870.88', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:54:17,332 >> {'loss': 1.697, 'grad_norm': 0.9408614039421082, 'learning_rate': 9.329475168076113e-06, 'epoch': 0.2584, 'num_input_tokens_seen': 1354760187, 'completed': '25.84% (323 / 1_250)', 'remaining time': '8:56:11', 'throughput': '117799.53', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:54:52,607 >> {'loss': 1.589, 'grad_norm': 0.24506370723247528, 'learning_rate': 9.322860706107875e-06, 'epoch': 0.2592, 'num_input_tokens_seen': 1358954491, 'completed': '25.92% (324 / 1_250)', 'remaining time': '8:55:37', 'throughput': '118902.51', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:55:27,900 >> {'loss': 1.5751, 'grad_norm': 1.1107831001281738, 'learning_rate': 9.316216432703918e-06, 'epoch': 0.26, 'num_input_tokens_seen': 1363148795, 'completed': '26.00% (325 / 1_250)', 'remaining time': '8:55:04', 'throughput': '118841.51', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:56:00,596 >> {'loss': 1.5797, 'grad_norm': 0.22349978983402252, 'learning_rate': 9.30954239967762e-06, 'epoch': 0.2608, 'num_input_tokens_seen': 1367343099, 'completed': '26.08% (326 / 1_250)', 'remaining time': '8:54:24', 'throughput': '128280.67', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:56:36,086 >> {'loss': 1.5988, 'grad_norm': 0.9254884719848633, 'learning_rate': 9.302838659074436e-06, 'epoch': 0.2616, 'num_input_tokens_seen': 1371537403, 'completed': '26.16% (327 / 1_250)', 'remaining time': '8:53:52', 'throughput': '118183.68', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:57:11,653 >> {'loss': 1.614, 'grad_norm': 0.6824395656585693, 'learning_rate': 9.296105263171476e-06, 'epoch': 0.2624, 'num_input_tokens_seen': 1375731707, 'completed': '26.24% (328 / 1_250)', 'remaining time': '8:53:19', 'throughput': '117928.63', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:57:46,172 >> {'loss': 1.6728, 'grad_norm': 0.7544028759002686, 'learning_rate': 9.289342264477116e-06, 'epoch': 0.2632, 'num_input_tokens_seen': 1379926011, 'completed': '26.32% (329 / 1_250)', 'remaining time': '8:52:44', 'throughput': '121506.87', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:58:21,270 >> {'loss': 1.7393, 'grad_norm': 0.9168422818183899, 'learning_rate': 9.282549715730579e-06, 'epoch': 0.264, 'num_input_tokens_seen': 1384120315, 'completed': '26.40% (330 / 1_250)', 'remaining time': '8:52:10', 'throughput': '119500.07', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:58:56,717 >> {'loss': 1.6199, 'grad_norm': 0.5892820358276367, 'learning_rate': 9.275727669901526e-06, 'epoch': 0.2648, 'num_input_tokens_seen': 1388314619, 'completed': '26.48% (331 / 1_250)', 'remaining time': '8:51:38', 'throughput': '118328.93', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 04:59:31,109 >> {'loss': 1.7292, 'grad_norm': 1.0376782417297363, 'learning_rate': 9.268876180189639e-06, 'epoch': 0.2656, 'num_input_tokens_seen': 1392508923, 'completed': '26.56% (332 / 1_250)', 'remaining time': '8:51:02', 'throughput': '121953.62', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:00:06,731 >> {'loss': 1.6118, 'grad_norm': 0.24416512250900269, 'learning_rate': 9.26199530002421e-06, 'epoch': 0.2664, 'num_input_tokens_seen': 1396703227, 'completed': '26.64% (333 / 1_250)', 'remaining time': '8:50:30', 'throughput': '117744.15', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:00:42,049 >> {'loss': 1.779, 'grad_norm': 0.9734512567520142, 'learning_rate': 9.255085083063726e-06, 'epoch': 0.2672, 'num_input_tokens_seen': 1400897531, 'completed': '26.72% (334 / 1_250)', 'remaining time': '8:49:57', 'throughput': '118758.16', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:01:13,312 >> {'loss': 1.7429, 'grad_norm': 0.23787687718868256, 'learning_rate': 9.248145583195449e-06, 'epoch': 0.268, 'num_input_tokens_seen': 1405091835, 'completed': '26.80% (335 / 1_250)', 'remaining time': '8:49:13', 'throughput': '134162.31', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:01:45,766 >> {'loss': 1.6284, 'grad_norm': 0.7830002307891846, 'learning_rate': 9.24117685453499e-06, 'epoch': 0.2688, 'num_input_tokens_seen': 1409286139, 'completed': '26.88% (336 / 1_250)', 'remaining time': '8:48:32', 'throughput': '129239.51', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:02:21,179 >> {'loss': 1.6029, 'grad_norm': 0.3031654953956604, 'learning_rate': 9.234178951425894e-06, 'epoch': 0.2696, 'num_input_tokens_seen': 1413480443, 'completed': '26.96% (337 / 1_250)', 'remaining time': '8:47:59', 'throughput': '118440.49', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:02:56,553 >> {'loss': 1.6349, 'grad_norm': 0.6513487100601196, 'learning_rate': 9.22715192843922e-06, 'epoch': 0.2704, 'num_input_tokens_seen': 1417674747, 'completed': '27.04% (338 / 1_250)', 'remaining time': '8:47:26', 'throughput': '118569.52', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:03:31,937 >> {'loss': 1.6635, 'grad_norm': 0.38696104288101196, 'learning_rate': 9.2200958403731e-06, 'epoch': 0.2712, 'num_input_tokens_seen': 1421869051, 'completed': '27.12% (339 / 1_250)', 'remaining time': '8:46:53', 'throughput': '118536.93', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:04:06,548 >> {'loss': 1.527, 'grad_norm': 0.7603062987327576, 'learning_rate': 9.213010742252328e-06, 'epoch': 0.272, 'num_input_tokens_seen': 1426063355, 'completed': '27.20% (340 / 1_250)', 'remaining time': '8:46:18', 'throughput': '121182.67', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:04:41,898 >> {'loss': 1.6353, 'grad_norm': 0.33491644263267517, 'learning_rate': 9.205896689327923e-06, 'epoch': 0.2728, 'num_input_tokens_seen': 1430257659, 'completed': '27.28% (341 / 1_250)', 'remaining time': '8:45:46', 'throughput': '118652.11', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:05:16,835 >> {'loss': 1.7468, 'grad_norm': 0.5067339539527893, 'learning_rate': 9.1987537370767e-06, 'epoch': 0.2736, 'num_input_tokens_seen': 1434451963, 'completed': '27.36% (342 / 1_250)', 'remaining time': '8:45:11', 'throughput': '120054.20', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:05:50,554 >> {'loss': 1.7184, 'grad_norm': 1.2791979312896729, 'learning_rate': 9.191581941200832e-06, 'epoch': 0.2744, 'num_input_tokens_seen': 1438646267, 'completed': '27.44% (343 / 1_250)', 'remaining time': '8:44:34', 'throughput': '124390.11', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:06:25,807 >> {'loss': 1.6563, 'grad_norm': 0.8083409667015076, 'learning_rate': 9.184381357627425e-06, 'epoch': 0.2752, 'num_input_tokens_seen': 1442840571, 'completed': '27.52% (344 / 1_250)', 'remaining time': '8:44:01', 'throughput': '118974.83', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:07:01,139 >> {'loss': 1.5506, 'grad_norm': 0.7334516048431396, 'learning_rate': 9.177152042508079e-06, 'epoch': 0.276, 'num_input_tokens_seen': 1447034875, 'completed': '27.60% (345 / 1_250)', 'remaining time': '8:43:28', 'throughput': '118711.73', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:07:35,860 >> {'loss': 1.7895, 'grad_norm': 0.40361228585243225, 'learning_rate': 9.169894052218443e-06, 'epoch': 0.2768, 'num_input_tokens_seen': 1451229179, 'completed': '27.68% (346 / 1_250)', 'remaining time': '8:42:53', 'throughput': '120800.28', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:08:11,433 >> {'loss': 1.5689, 'grad_norm': 0.6642701029777527, 'learning_rate': 9.162607443357783e-06, 'epoch': 0.2776, 'num_input_tokens_seen': 1455423483, 'completed': '27.76% (347 / 1_250)', 'remaining time': '8:42:21', 'throughput': '117908.61', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:08:42,678 >> {'loss': 1.5758, 'grad_norm': 0.28694072365760803, 'learning_rate': 9.155292272748538e-06, 'epoch': 0.2784, 'num_input_tokens_seen': 1459617787, 'completed': '27.84% (348 / 1_250)', 'remaining time': '8:41:37', 'throughput': '134239.44', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:09:18,013 >> {'loss': 1.5497, 'grad_norm': 0.5333842039108276, 'learning_rate': 9.14794859743588e-06, 'epoch': 0.2792, 'num_input_tokens_seen': 1463812091, 'completed': '27.92% (349 / 1_250)', 'remaining time': '8:41:04', 'throughput': '118701.44', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:09:52,177 >> {'loss': 1.6669, 'grad_norm': 0.6278814077377319, 'learning_rate': 9.140576474687263e-06, 'epoch': 0.28, 'num_input_tokens_seen': 1468006395, 'completed': '28.00% (350 / 1_250)', 'remaining time': '8:40:28', 'throughput': '122767.50', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:10:27,572 >> {'loss': 1.5772, 'grad_norm': 0.8230255842208862, 'learning_rate': 9.133175961991984e-06, 'epoch': 0.2808, 'num_input_tokens_seen': 1472200699, 'completed': '28.08% (351 / 1_250)', 'remaining time': '8:39:55', 'throughput': '118499.31', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:11:01,626 >> {'loss': 1.5482, 'grad_norm': 0.7572386264801025, 'learning_rate': 9.125747117060722e-06, 'epoch': 0.2816, 'num_input_tokens_seen': 1476395003, 'completed': '28.16% (352 / 1_250)', 'remaining time': '8:39:19', 'throughput': '123165.74', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:11:37,150 >> {'loss': 1.7279, 'grad_norm': 1.0967744588851929, 'learning_rate': 9.118289997825105e-06, 'epoch': 0.2824, 'num_input_tokens_seen': 1480589306, 'completed': '28.24% (353 / 1_250)', 'remaining time': '8:38:46', 'throughput': '118069.85', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:12:12,803 >> {'loss': 1.6952, 'grad_norm': 0.8018703460693359, 'learning_rate': 9.110804662437251e-06, 'epoch': 0.2832, 'num_input_tokens_seen': 1484783610, 'completed': '28.32% (354 / 1_250)', 'remaining time': '8:38:14', 'throughput': '117643.07', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:12:48,167 >> {'loss': 1.6024, 'grad_norm': 0.73807692527771, 'learning_rate': 9.1032911692693e-06, 'epoch': 0.284, 'num_input_tokens_seen': 1488977914, 'completed': '28.40% (355 / 1_250)', 'remaining time': '8:37:41', 'throughput': '118604.28', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:13:19,531 >> {'loss': 1.6652, 'grad_norm': 0.8086133003234863, 'learning_rate': 9.09574957691299e-06, 'epoch': 0.2848, 'num_input_tokens_seen': 1493172218, 'completed': '28.48% (356 / 1_250)', 'remaining time': '8:36:58', 'throughput': '133729.24', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:13:54,841 >> {'loss': 1.4856, 'grad_norm': 0.42226120829582214, 'learning_rate': 9.088179944179166e-06, 'epoch': 0.2856, 'num_input_tokens_seen': 1497366522, 'completed': '28.56% (357 / 1_250)', 'remaining time': '8:36:24', 'throughput': '118785.98', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:14:30,028 >> {'loss': 1.7833, 'grad_norm': 1.088250994682312, 'learning_rate': 9.080582330097349e-06, 'epoch': 0.2864, 'num_input_tokens_seen': 1501560826, 'completed': '28.64% (358 / 1_250)', 'remaining time': '8:35:51', 'throughput': '119201.42', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:15:05,106 >> {'loss': 1.6931, 'grad_norm': 0.362918883562088, 'learning_rate': 9.07295679391526e-06, 'epoch': 0.2872, 'num_input_tokens_seen': 1505755130, 'completed': '28.72% (359 / 1_250)', 'remaining time': '8:35:17', 'throughput': '119569.35', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:15:40,434 >> {'loss': 1.6491, 'grad_norm': 0.46381181478500366, 'learning_rate': 9.06530339509836e-06, 'epoch': 0.288, 'num_input_tokens_seen': 1509949434, 'completed': '28.80% (360 / 1_250)', 'remaining time': '8:34:44', 'throughput': '118723.43', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:16:11,130 >> {'loss': 1.6323, 'grad_norm': 0.5881064534187317, 'learning_rate': 9.05762219332939e-06, 'epoch': 0.2888, 'num_input_tokens_seen': 1514143738, 'completed': '28.88% (361 / 1_250)', 'remaining time': '8:33:59', 'throughput': '136643.01', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:16:46,349 >> {'loss': 1.6588, 'grad_norm': 0.5754746198654175, 'learning_rate': 9.049913248507905e-06, 'epoch': 0.2896, 'num_input_tokens_seen': 1518338042, 'completed': '28.96% (362 / 1_250)', 'remaining time': '8:33:26', 'throughput': '119091.42', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:17:20,486 >> {'loss': 1.6025, 'grad_norm': 0.44729363918304443, 'learning_rate': 9.042176620749805e-06, 'epoch': 0.2904, 'num_input_tokens_seen': 1522532346, 'completed': '29.04% (363 / 1_250)', 'remaining time': '8:32:50', 'throughput': '122866.40', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:17:54,569 >> {'loss': 1.6481, 'grad_norm': 0.43016770482063293, 'learning_rate': 9.03441237038687e-06, 'epoch': 0.2912, 'num_input_tokens_seen': 1526726650, 'completed': '29.12% (364 / 1_250)', 'remaining time': '8:32:14', 'throughput': '123062.49', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:18:29,604 >> {'loss': 1.5235, 'grad_norm': 0.47520187497138977, 'learning_rate': 9.02662055796628e-06, 'epoch': 0.292, 'num_input_tokens_seen': 1530920954, 'completed': '29.20% (365 / 1_250)', 'remaining time': '8:31:40', 'throughput': '119716.08', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:19:04,889 >> {'loss': 1.7646, 'grad_norm': 0.604560136795044, 'learning_rate': 9.018801244250157e-06, 'epoch': 0.2928, 'num_input_tokens_seen': 1535115257, 'completed': '29.28% (366 / 1_250)', 'remaining time': '8:31:07', 'throughput': '118870.66', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:19:35,823 >> {'loss': 1.7817, 'grad_norm': 0.3712136745452881, 'learning_rate': 9.010954490215077e-06, 'epoch': 0.2936, 'num_input_tokens_seen': 1539309561, 'completed': '29.36% (367 / 1_250)', 'remaining time': '8:30:23', 'throughput': '135586.98', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:20:11,039 >> {'loss': 1.6537, 'grad_norm': 0.8315712213516235, 'learning_rate': 9.003080357051606e-06, 'epoch': 0.2944, 'num_input_tokens_seen': 1543503865, 'completed': '29.44% (368 / 1_250)', 'remaining time': '8:29:50', 'throughput': '119104.52', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:20:46,567 >> {'loss': 1.414, 'grad_norm': 0.578404426574707, 'learning_rate': 8.995178906163817e-06, 'epoch': 0.2952, 'num_input_tokens_seen': 1547698169, 'completed': '29.52% (369 / 1_250)', 'remaining time': '8:29:17', 'throughput': '118053.40', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:21:22,034 >> {'loss': 1.5534, 'grad_norm': 0.3666025400161743, 'learning_rate': 8.98725019916881e-06, 'epoch': 0.296, 'num_input_tokens_seen': 1551892473, 'completed': '29.60% (370 / 1_250)', 'remaining time': '8:28:44', 'throughput': '118262.21', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:21:57,356 >> {'loss': 1.8783, 'grad_norm': 0.7067350745201111, 'learning_rate': 8.979294297896233e-06, 'epoch': 0.2968, 'num_input_tokens_seen': 1556086777, 'completed': '29.68% (371 / 1_250)', 'remaining time': '8:28:11', 'throughput': '118743.71', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:22:32,802 >> {'loss': 1.4524, 'grad_norm': 0.40672728419303894, 'learning_rate': 8.971311264387806e-06, 'epoch': 0.2976, 'num_input_tokens_seen': 1560281081, 'completed': '29.76% (372 / 1_250)', 'remaining time': '8:27:38', 'throughput': '118327.43', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:23:06,821 >> {'loss': 1.4323, 'grad_norm': 0.8277244567871094, 'learning_rate': 8.963301160896826e-06, 'epoch': 0.2984, 'num_input_tokens_seen': 1564475385, 'completed': '29.84% (373 / 1_250)', 'remaining time': '8:27:02', 'throughput': '123295.08', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:23:42,192 >> {'loss': 1.437, 'grad_norm': 0.26989346742630005, 'learning_rate': 8.95526404988769e-06, 'epoch': 0.2992, 'num_input_tokens_seen': 1568669689, 'completed': '29.92% (374 / 1_250)', 'remaining time': '8:26:29', 'throughput': '118581.33', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:24:17,539 >> {'loss': 1.7673, 'grad_norm': 1.1804054975509644, 'learning_rate': 8.947199994035402e-06, 'epoch': 0.3, 'num_input_tokens_seen': 1572863993, 'completed': '30.00% (375 / 1_250)', 'remaining time': '8:25:56', 'throughput': '118659.49', 'gpu_mem_free': '16314MB'} +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:689: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +[INFO|trainer.py:3503] 2026-05-02 05:24:25,663 >> Saving model checkpoint to /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-375 +[INFO|configuration_utils.py:472] 2026-05-02 05:24:25,665 >> Configuration saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-375/config.json +[INFO|configuration_utils.py:807] 2026-05-02 05:24:25,665 >> Configuration saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-375/generation_config.json +[INFO|modeling_utils.py:2807] 2026-05-02 05:24:37,445 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 3 checkpoint shards. You can find where each parameters has been saved in the index located at /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-375/model.safetensors.index.json. +[INFO|tokenization_utils_base.py:2684] 2026-05-02 05:24:37,447 >> tokenizer config file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-375/tokenizer_config.json +[INFO|tokenization_utils_base.py:2693] 2026-05-02 05:24:37,447 >> Special tokens file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-375/special_tokens_map.json +[INFO|tokenization_utils_base.py:2684] 2026-05-02 05:24:45,971 >> tokenizer config file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/tokenizer_config.json +[INFO|tokenization_utils_base.py:2693] 2026-05-02 05:24:45,971 >> Special tokens file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/special_tokens_map.json +[INFO|trainer.py:3595] 2026-05-02 05:24:45,976 >> Deleting older checkpoint [/tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-250] due to args.save_total_limit +[WARNING|trainer.py:870] 2026-05-02 05:24:47,218 >> Save streaming dataset state: {'epoch': 0, 'sample_in_epoch': 96000, 'num_canonical_nodes': 2, 'shuffle_seed': 42, 'initial_physical_nodes': 2} +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/utils/checkpoint.py:1399: FutureWarning: `torch.cpu.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cpu', args...)` instead. + with device_autocast_ctx, torch.cpu.amp.autocast(**cpu_autocast_kwargs), recompute_context: # type: ignore[attr-defined] +[INFO|trainer.py:175] 2026-05-02 05:25:17,602 >> {'loss': 1.5321, 'grad_norm': 0.3814813792705536, 'learning_rate': 8.93910905622509e-06, 'epoch': 0.3008, 'num_input_tokens_seen': 1577058297, 'completed': '30.08% (376 / 1_250)', 'remaining time': '8:26:20', 'throughput': '69832.00', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:25:50,671 >> {'loss': 1.5102, 'grad_norm': 0.76215660572052, 'learning_rate': 8.930991299551516e-06, 'epoch': 0.3016, 'num_input_tokens_seen': 1581252601, 'completed': '30.16% (377 / 1_250)', 'remaining time': '8:25:41', 'throughput': '126833.84', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:26:22,319 >> {'loss': 1.7091, 'grad_norm': 0.3180020749568939, 'learning_rate': 8.922846787318572e-06, 'epoch': 0.3024, 'num_input_tokens_seen': 1585446905, 'completed': '30.24% (378 / 1_250)', 'remaining time': '8:24:59', 'throughput': '132531.28', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:26:57,633 >> {'loss': 1.5782, 'grad_norm': 0.6570141315460205, 'learning_rate': 8.914675583038806e-06, 'epoch': 0.3032, 'num_input_tokens_seen': 1589641209, 'completed': '30.32% (379 / 1_250)', 'remaining time': '8:24:26', 'throughput': '118772.15', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:27:32,862 >> {'loss': 1.7973, 'grad_norm': 0.42125609517097473, 'learning_rate': 8.906477750432904e-06, 'epoch': 0.304, 'num_input_tokens_seen': 1593835513, 'completed': '30.40% (380 / 1_250)', 'remaining time': '8:23:52', 'throughput': '119055.51', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:28:08,350 >> {'loss': 1.4283, 'grad_norm': 0.7137016654014587, 'learning_rate': 8.898253353429216e-06, 'epoch': 0.3048, 'num_input_tokens_seen': 1598029817, 'completed': '30.48% (381 / 1_250)', 'remaining time': '8:23:19', 'throughput': '118191.22', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:28:43,996 >> {'loss': 1.6588, 'grad_norm': 0.8452203869819641, 'learning_rate': 8.890002456163241e-06, 'epoch': 0.3056, 'num_input_tokens_seen': 1602224121, 'completed': '30.56% (382 / 1_250)', 'remaining time': '8:22:46', 'throughput': '117665.15', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:29:19,138 >> {'loss': 1.5978, 'grad_norm': 0.424259215593338, 'learning_rate': 8.881725122977132e-06, 'epoch': 0.3064, 'num_input_tokens_seen': 1606418425, 'completed': '30.64% (383 / 1_250)', 'remaining time': '8:22:12', 'throughput': '119351.32', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:29:54,281 >> {'loss': 1.4692, 'grad_norm': 0.7589101195335388, 'learning_rate': 8.873421418419198e-06, 'epoch': 0.3072, 'num_input_tokens_seen': 1610612729, 'completed': '30.72% (384 / 1_250)', 'remaining time': '8:21:39', 'throughput': '119351.83', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:30:29,501 >> {'loss': 1.925, 'grad_norm': 0.526006281375885, 'learning_rate': 8.865091407243395e-06, 'epoch': 0.308, 'num_input_tokens_seen': 1614807033, 'completed': '30.80% (385 / 1_250)', 'remaining time': '8:21:05', 'throughput': '119087.32', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:31:05,062 >> {'loss': 1.5065, 'grad_norm': 1.2128034830093384, 'learning_rate': 8.856735154408821e-06, 'epoch': 0.3088, 'num_input_tokens_seen': 1619001337, 'completed': '30.88% (386 / 1_250)', 'remaining time': '8:20:32', 'throughput': '117948.35', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:31:39,360 >> {'loss': 1.7657, 'grad_norm': 0.6558699011802673, 'learning_rate': 8.848352725079216e-06, 'epoch': 0.3096, 'num_input_tokens_seen': 1623195641, 'completed': '30.96% (387 / 1_250)', 'remaining time': '8:19:56', 'throughput': '122289.58', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:32:14,840 >> {'loss': 1.9782, 'grad_norm': 1.1497911214828491, 'learning_rate': 8.839944184622447e-06, 'epoch': 0.3104, 'num_input_tokens_seen': 1627389945, 'completed': '31.04% (388 / 1_250)', 'remaining time': '8:19:23', 'throughput': '118214.98', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:32:50,120 >> {'loss': 1.5042, 'grad_norm': 0.525629460811615, 'learning_rate': 8.831509598610001e-06, 'epoch': 0.3112, 'num_input_tokens_seen': 1631584249, 'completed': '31.12% (389 / 1_250)', 'remaining time': '8:18:49', 'throughput': '118886.39', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:33:25,413 >> {'loss': 1.5404, 'grad_norm': 0.7008910775184631, 'learning_rate': 8.823049032816478e-06, 'epoch': 0.312, 'num_input_tokens_seen': 1635778553, 'completed': '31.20% (390 / 1_250)', 'remaining time': '8:18:16', 'throughput': '118843.07', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:33:56,621 >> {'loss': 1.7233, 'grad_norm': 1.1060113906860352, 'learning_rate': 8.814562553219066e-06, 'epoch': 0.3128, 'num_input_tokens_seen': 1639972857, 'completed': '31.28% (391 / 1_250)', 'remaining time': '8:17:33', 'throughput': '134399.32', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:34:32,125 >> {'loss': 1.5049, 'grad_norm': 0.227466881275177, 'learning_rate': 8.806050225997039e-06, 'epoch': 0.3136, 'num_input_tokens_seen': 1644167161, 'completed': '31.36% (392 / 1_250)', 'remaining time': '8:17:00', 'throughput': '118134.09', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:35:02,714 >> {'loss': 1.5178, 'grad_norm': 0.6808207035064697, 'learning_rate': 8.79751211753123e-06, 'epoch': 0.3144, 'num_input_tokens_seen': 1648361465, 'completed': '31.44% (393 / 1_250)', 'remaining time': '8:16:16', 'throughput': '137118.48', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:35:38,089 >> {'loss': 1.5503, 'grad_norm': 0.69118732213974, 'learning_rate': 8.788948294403532e-06, 'epoch': 0.3152, 'num_input_tokens_seen': 1652555769, 'completed': '31.52% (394 / 1_250)', 'remaining time': '8:15:43', 'throughput': '118568.48', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:36:13,455 >> {'loss': 1.5415, 'grad_norm': 0.6170138120651245, 'learning_rate': 8.780358823396352e-06, 'epoch': 0.316, 'num_input_tokens_seen': 1656750073, 'completed': '31.60% (395 / 1_250)', 'remaining time': '8:15:09', 'throughput': '118596.47', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:36:44,159 >> {'loss': 1.7026, 'grad_norm': 1.0461091995239258, 'learning_rate': 8.771743771492113e-06, 'epoch': 0.3168, 'num_input_tokens_seen': 1660944377, 'completed': '31.68% (396 / 1_250)', 'remaining time': '8:14:26', 'throughput': '136606.08', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:37:19,596 >> {'loss': 1.6752, 'grad_norm': 0.4433194100856781, 'learning_rate': 8.76310320587272e-06, 'epoch': 0.3176, 'num_input_tokens_seen': 1665138681, 'completed': '31.76% (397 / 1_250)', 'remaining time': '8:13:53', 'throughput': '118358.71', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:37:55,318 >> {'loss': 1.5754, 'grad_norm': 0.7948556542396545, 'learning_rate': 8.75443719391904e-06, 'epoch': 0.3184, 'num_input_tokens_seen': 1669332985, 'completed': '31.84% (398 / 1_250)', 'remaining time': '8:13:20', 'throughput': '117415.58', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:38:30,624 >> {'loss': 1.7137, 'grad_norm': 0.5654433369636536, 'learning_rate': 8.745745803210374e-06, 'epoch': 0.3192, 'num_input_tokens_seen': 1673527289, 'completed': '31.92% (399 / 1_250)', 'remaining time': '8:12:47', 'throughput': '118798.62', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:39:06,334 >> {'loss': 1.6232, 'grad_norm': 0.7628309726715088, 'learning_rate': 8.737029101523931e-06, 'epoch': 0.32, 'num_input_tokens_seen': 1677721593, 'completed': '32.00% (400 / 1_250)', 'remaining time': '8:12:14', 'throughput': '117452.85', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:39:41,825 >> {'loss': 1.6315, 'grad_norm': 0.689399778842926, 'learning_rate': 8.728287156834305e-06, 'epoch': 0.3208, 'num_input_tokens_seen': 1681915897, 'completed': '32.08% (401 / 1_250)', 'remaining time': '8:11:41', 'throughput': '118179.50', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:40:17,256 >> {'loss': 1.5712, 'grad_norm': 0.25623756647109985, 'learning_rate': 8.719520037312934e-06, 'epoch': 0.3216, 'num_input_tokens_seen': 1686110201, 'completed': '32.16% (402 / 1_250)', 'remaining time': '8:11:07', 'throughput': '118378.45', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:40:48,944 >> {'loss': 1.5323, 'grad_norm': 0.6536148190498352, 'learning_rate': 8.71072781132758e-06, 'epoch': 0.3224, 'num_input_tokens_seen': 1690304504, 'completed': '32.24% (403 / 1_250)', 'remaining time': '8:10:26', 'throughput': '132364.76', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:41:24,444 >> {'loss': 1.5998, 'grad_norm': 0.661840558052063, 'learning_rate': 8.701910547441786e-06, 'epoch': 0.3232, 'num_input_tokens_seen': 1694498808, 'completed': '32.32% (404 / 1_250)', 'remaining time': '8:09:53', 'throughput': '118149.28', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:41:59,990 >> {'loss': 1.5423, 'grad_norm': 0.6132088303565979, 'learning_rate': 8.693068314414345e-06, 'epoch': 0.324, 'num_input_tokens_seen': 1698693112, 'completed': '32.40% (405 / 1_250)', 'remaining time': '8:09:20', 'throughput': '117997.02', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:42:35,291 >> {'loss': 1.6123, 'grad_norm': 0.7426416277885437, 'learning_rate': 8.684201181198769e-06, 'epoch': 0.3248, 'num_input_tokens_seen': 1702887416, 'completed': '32.48% (406 / 1_250)', 'remaining time': '8:08:46', 'throughput': '118814.39', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:43:10,753 >> {'loss': 1.6757, 'grad_norm': 0.39316752552986145, 'learning_rate': 8.675309216942744e-06, 'epoch': 0.3256, 'num_input_tokens_seen': 1707081720, 'completed': '32.56% (407 / 1_250)', 'remaining time': '8:08:13', 'throughput': '118277.16', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:43:45,968 >> {'loss': 1.7612, 'grad_norm': 0.6175826191902161, 'learning_rate': 8.666392490987592e-06, 'epoch': 0.3264, 'num_input_tokens_seen': 1711276024, 'completed': '32.64% (408 / 1_250)', 'remaining time': '8:07:39', 'throughput': '119104.57', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:44:21,264 >> {'loss': 1.8207, 'grad_norm': 0.2766948938369751, 'learning_rate': 8.657451072867735e-06, 'epoch': 0.3272, 'num_input_tokens_seen': 1715470327, 'completed': '32.72% (409 / 1_250)', 'remaining time': '8:07:06', 'throughput': '118833.60', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:44:56,722 >> {'loss': 1.6084, 'grad_norm': 0.4224601984024048, 'learning_rate': 8.648485032310146e-06, 'epoch': 0.328, 'num_input_tokens_seen': 1719664631, 'completed': '32.80% (410 / 1_250)', 'remaining time': '8:06:32', 'throughput': '118286.99', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:45:31,794 >> {'loss': 1.5658, 'grad_norm': 0.2843654453754425, 'learning_rate': 8.639494439233808e-06, 'epoch': 0.3288, 'num_input_tokens_seen': 1723858935, 'completed': '32.88% (411 / 1_250)', 'remaining time': '8:05:58', 'throughput': '119591.33', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:46:07,423 >> {'loss': 1.5988, 'grad_norm': 0.3726174235343933, 'learning_rate': 8.630479363749179e-06, 'epoch': 0.3296, 'num_input_tokens_seen': 1728053239, 'completed': '32.96% (412 / 1_250)', 'remaining time': '8:05:25', 'throughput': '117722.53', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:46:40,375 >> {'loss': 1.4943, 'grad_norm': 0.19656279683113098, 'learning_rate': 8.621439876157623e-06, 'epoch': 0.3304, 'num_input_tokens_seen': 1732247543, 'completed': '33.04% (413 / 1_250)', 'remaining time': '8:04:47', 'throughput': '127285.19', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:47:14,836 >> {'loss': 1.7274, 'grad_norm': 0.9217410087585449, 'learning_rate': 8.61237604695088e-06, 'epoch': 0.3312, 'num_input_tokens_seen': 1736441847, 'completed': '33.12% (414 / 1_250)', 'remaining time': '8:04:12', 'throughput': '121713.66', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:47:50,154 >> {'loss': 1.7819, 'grad_norm': 0.5389394164085388, 'learning_rate': 8.603287946810515e-06, 'epoch': 0.332, 'num_input_tokens_seen': 1740636151, 'completed': '33.20% (415 / 1_250)', 'remaining time': '8:03:38', 'throughput': '118757.73', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:48:21,388 >> {'loss': 1.6624, 'grad_norm': 0.39544081687927246, 'learning_rate': 8.594175646607354e-06, 'epoch': 0.3328, 'num_input_tokens_seen': 1744830455, 'completed': '33.28% (416 / 1_250)', 'remaining time': '8:02:56', 'throughput': '134284.42', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:48:56,677 >> {'loss': 1.6793, 'grad_norm': 0.617043137550354, 'learning_rate': 8.585039217400947e-06, 'epoch': 0.3336, 'num_input_tokens_seen': 1749024759, 'completed': '33.36% (417 / 1_250)', 'remaining time': '8:02:23', 'throughput': '118857.33', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:49:28,822 >> {'loss': 1.6497, 'grad_norm': 0.3316190540790558, 'learning_rate': 8.575878730439003e-06, 'epoch': 0.3344, 'num_input_tokens_seen': 1753219063, 'completed': '33.44% (418 / 1_250)', 'remaining time': '8:01:43', 'throughput': '130480.52', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:50:04,237 >> {'loss': 1.6235, 'grad_norm': 0.4609556794166565, 'learning_rate': 8.56669425715684e-06, 'epoch': 0.3352, 'num_input_tokens_seen': 1757413367, 'completed': '33.52% (419 / 1_250)', 'remaining time': '8:01:09', 'throughput': '118431.37', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:50:38,767 >> {'loss': 1.5845, 'grad_norm': 0.4462856948375702, 'learning_rate': 8.557485869176826e-06, 'epoch': 0.336, 'num_input_tokens_seen': 1761607671, 'completed': '33.60% (420 / 1_250)', 'remaining time': '8:00:34', 'throughput': '121468.31', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:51:14,245 >> {'loss': 1.5995, 'grad_norm': 0.2537747323513031, 'learning_rate': 8.548253638307819e-06, 'epoch': 0.3368, 'num_input_tokens_seen': 1765801975, 'completed': '33.68% (421 / 1_250)', 'remaining time': '8:00:01', 'throughput': '118223.03', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:51:49,400 >> {'loss': 1.6057, 'grad_norm': 0.6053887605667114, 'learning_rate': 8.53899763654461e-06, 'epoch': 0.3376, 'num_input_tokens_seen': 1769996279, 'completed': '33.76% (422 / 1_250)', 'remaining time': '7:59:27', 'throughput': '119308.86', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:52:24,772 >> {'loss': 1.4556, 'grad_norm': 0.4941142499446869, 'learning_rate': 8.529717936067363e-06, 'epoch': 0.3384, 'num_input_tokens_seen': 1774190583, 'completed': '33.84% (423 / 1_250)', 'remaining time': '7:58:53', 'throughput': '118576.98', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:52:59,646 >> {'loss': 1.7929, 'grad_norm': 0.5307502150535583, 'learning_rate': 8.520414609241042e-06, 'epoch': 0.3392, 'num_input_tokens_seen': 1778384887, 'completed': '33.92% (424 / 1_250)', 'remaining time': '7:58:19', 'throughput': '120269.41', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:53:34,904 >> {'loss': 1.5053, 'grad_norm': 0.34676700830459595, 'learning_rate': 8.511087728614863e-06, 'epoch': 0.34, 'num_input_tokens_seen': 1782579191, 'completed': '34.00% (425 / 1_250)', 'remaining time': '7:57:45', 'throughput': '118962.78', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:54:07,459 >> {'loss': 1.5141, 'grad_norm': 0.5079925656318665, 'learning_rate': 8.501737366921711e-06, 'epoch': 0.3408, 'num_input_tokens_seen': 1786773495, 'completed': '34.08% (426 / 1_250)', 'remaining time': '7:57:06', 'throughput': '128836.00', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:54:42,937 >> {'loss': 1.5716, 'grad_norm': 0.27891334891319275, 'learning_rate': 8.492363597077586e-06, 'epoch': 0.3416, 'num_input_tokens_seen': 1790967799, 'completed': '34.16% (427 / 1_250)', 'remaining time': '7:56:33', 'throughput': '118223.25', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:55:18,326 >> {'loss': 1.7241, 'grad_norm': 0.46924394369125366, 'learning_rate': 8.48296649218103e-06, 'epoch': 0.3424, 'num_input_tokens_seen': 1795162103, 'completed': '34.24% (428 / 1_250)', 'remaining time': '7:55:59', 'throughput': '118519.85', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:55:53,763 >> {'loss': 1.6445, 'grad_norm': 0.2996901869773865, 'learning_rate': 8.473546125512551e-06, 'epoch': 0.3432, 'num_input_tokens_seen': 1799356407, 'completed': '34.32% (429 / 1_250)', 'remaining time': '7:55:26', 'throughput': '118357.70', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:56:29,324 >> {'loss': 1.5973, 'grad_norm': 0.4557002782821655, 'learning_rate': 8.464102570534063e-06, 'epoch': 0.344, 'num_input_tokens_seen': 1803550711, 'completed': '34.40% (430 / 1_250)', 'remaining time': '7:54:53', 'throughput': '117946.66', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:57:04,819 >> {'loss': 1.3712, 'grad_norm': 0.3522830605506897, 'learning_rate': 8.454635900888304e-06, 'epoch': 0.3448, 'num_input_tokens_seen': 1807745015, 'completed': '34.48% (431 / 1_250)', 'remaining time': '7:54:19', 'throughput': '118168.55', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:57:40,078 >> {'loss': 1.506, 'grad_norm': 0.3508545458316803, 'learning_rate': 8.445146190398267e-06, 'epoch': 0.3456, 'num_input_tokens_seen': 1811939319, 'completed': '34.56% (432 / 1_250)', 'remaining time': '7:53:46', 'throughput': '118956.82', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:58:15,382 >> {'loss': 1.668, 'grad_norm': 0.35032346844673157, 'learning_rate': 8.43563351306662e-06, 'epoch': 0.3464, 'num_input_tokens_seen': 1816133623, 'completed': '34.64% (433 / 1_250)', 'remaining time': '7:53:12', 'throughput': '118805.04', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:58:49,827 >> {'loss': 1.5906, 'grad_norm': 0.2786749005317688, 'learning_rate': 8.42609794307513e-06, 'epoch': 0.3472, 'num_input_tokens_seen': 1820327927, 'completed': '34.72% (434 / 1_250)', 'remaining time': '7:52:36', 'throughput': '121767.02', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 05:59:25,138 >> {'loss': 1.472, 'grad_norm': 0.6916569471359253, 'learning_rate': 8.41653955478409e-06, 'epoch': 0.348, 'num_input_tokens_seen': 1824522231, 'completed': '34.80% (435 / 1_250)', 'remaining time': '7:52:03', 'throughput': '118780.92', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:00:00,608 >> {'loss': 1.5188, 'grad_norm': 0.23510178923606873, 'learning_rate': 8.406958422731731e-06, 'epoch': 0.3488, 'num_input_tokens_seen': 1828716535, 'completed': '34.88% (436 / 1_250)', 'remaining time': '7:51:29', 'throughput': '118250.59', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:00:34,617 >> {'loss': 1.8797, 'grad_norm': 0.5385719537734985, 'learning_rate': 8.397354621633644e-06, 'epoch': 0.3496, 'num_input_tokens_seen': 1832910839, 'completed': '34.96% (437 / 1_250)', 'remaining time': '7:50:53', 'throughput': '123329.36', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:01:08,740 >> {'loss': 1.573, 'grad_norm': 0.653972864151001, 'learning_rate': 8.387728226382199e-06, 'epoch': 0.3504, 'num_input_tokens_seen': 1837105143, 'completed': '35.04% (438 / 1_250)', 'remaining time': '7:50:17', 'throughput': '122918.10', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:01:44,083 >> {'loss': 1.8513, 'grad_norm': 0.33440396189689636, 'learning_rate': 8.378079312045961e-06, 'epoch': 0.3512, 'num_input_tokens_seen': 1841299447, 'completed': '35.12% (439 / 1_250)', 'remaining time': '7:49:44', 'throughput': '118671.93', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:02:15,231 >> {'loss': 1.7798, 'grad_norm': 0.4884359836578369, 'learning_rate': 8.368407953869105e-06, 'epoch': 0.352, 'num_input_tokens_seen': 1845493751, 'completed': '35.20% (440 / 1_250)', 'remaining time': '7:49:02', 'throughput': '134657.82', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:02:50,693 >> {'loss': 1.5459, 'grad_norm': 0.45464232563972473, 'learning_rate': 8.35871422727082e-06, 'epoch': 0.3528, 'num_input_tokens_seen': 1849688055, 'completed': '35.28% (441 / 1_250)', 'remaining time': '7:48:29', 'throughput': '118277.85', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:03:24,300 >> {'loss': 1.6989, 'grad_norm': 0.3229081630706787, 'learning_rate': 8.348998207844737e-06, 'epoch': 0.3536, 'num_input_tokens_seen': 1853882359, 'completed': '35.36% (442 / 1_250)', 'remaining time': '7:47:52', 'throughput': '124804.74', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:03:56,590 >> {'loss': 1.4759, 'grad_norm': 0.325906902551651, 'learning_rate': 8.339259971358325e-06, 'epoch': 0.3544, 'num_input_tokens_seen': 1858076663, 'completed': '35.44% (443 / 1_250)', 'remaining time': '7:47:13', 'throughput': '129894.14', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:04:31,936 >> {'loss': 1.5194, 'grad_norm': 0.24602539837360382, 'learning_rate': 8.329499593752308e-06, 'epoch': 0.3552, 'num_input_tokens_seen': 1862270967, 'completed': '35.52% (444 / 1_250)', 'remaining time': '7:46:39', 'throughput': '118662.96', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:05:07,143 >> {'loss': 1.6445, 'grad_norm': 0.30536580085754395, 'learning_rate': 8.319717151140072e-06, 'epoch': 0.356, 'num_input_tokens_seen': 1866465271, 'completed': '35.60% (445 / 1_250)', 'remaining time': '7:46:05', 'throughput': '119132.61', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:05:42,584 >> {'loss': 1.452, 'grad_norm': 0.4427531063556671, 'learning_rate': 8.309912719807072e-06, 'epoch': 0.3568, 'num_input_tokens_seen': 1870659575, 'completed': '35.68% (446 / 1_250)', 'remaining time': '7:45:32', 'throughput': '118347.42', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:06:18,006 >> {'loss': 1.6041, 'grad_norm': 0.7691037654876709, 'learning_rate': 8.30008637621023e-06, 'epoch': 0.3576, 'num_input_tokens_seen': 1874853879, 'completed': '35.76% (447 / 1_250)', 'remaining time': '7:44:58', 'throughput': '118408.19', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:06:53,194 >> {'loss': 1.6566, 'grad_norm': 0.5166177749633789, 'learning_rate': 8.290238196977347e-06, 'epoch': 0.3584, 'num_input_tokens_seen': 1879048183, 'completed': '35.84% (448 / 1_250)', 'remaining time': '7:44:24', 'throughput': '119197.55', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:07:28,296 >> {'loss': 1.5538, 'grad_norm': 0.5728665590286255, 'learning_rate': 8.280368258906507e-06, 'epoch': 0.3592, 'num_input_tokens_seen': 1883242487, 'completed': '35.92% (449 / 1_250)', 'remaining time': '7:43:50', 'throughput': '119488.87', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:08:03,595 >> {'loss': 1.6189, 'grad_norm': 0.3069063127040863, 'learning_rate': 8.270476638965463e-06, 'epoch': 0.36, 'num_input_tokens_seen': 1887436791, 'completed': '36.00% (450 / 1_250)', 'remaining time': '7:43:16', 'throughput': '118823.77', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:08:39,022 >> {'loss': 1.5214, 'grad_norm': 0.34531405568122864, 'learning_rate': 8.260563414291059e-06, 'epoch': 0.3608, 'num_input_tokens_seen': 1891631095, 'completed': '36.08% (451 / 1_250)', 'remaining time': '7:42:43', 'throughput': '118393.12', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:09:14,463 >> {'loss': 1.6059, 'grad_norm': 0.2583816945552826, 'learning_rate': 8.250628662188613e-06, 'epoch': 0.3616, 'num_input_tokens_seen': 1895825399, 'completed': '36.16% (452 / 1_250)', 'remaining time': '7:42:09', 'throughput': '118344.18', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:09:49,626 >> {'loss': 1.7787, 'grad_norm': 0.5631863474845886, 'learning_rate': 8.240672460131315e-06, 'epoch': 0.3624, 'num_input_tokens_seen': 1900019703, 'completed': '36.24% (453 / 1_250)', 'remaining time': '7:41:35', 'throughput': '119283.36', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:10:23,981 >> {'loss': 1.6941, 'grad_norm': 0.49435651302337646, 'learning_rate': 8.230694885759632e-06, 'epoch': 0.3632, 'num_input_tokens_seen': 1904214007, 'completed': '36.32% (454 / 1_250)', 'remaining time': '7:41:00', 'throughput': '122086.58', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:10:59,379 >> {'loss': 1.6093, 'grad_norm': 0.2892875373363495, 'learning_rate': 8.220696016880689e-06, 'epoch': 0.364, 'num_input_tokens_seen': 1908408311, 'completed': '36.40% (455 / 1_250)', 'remaining time': '7:40:26', 'throughput': '118487.95', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:11:34,695 >> {'loss': 1.7911, 'grad_norm': 0.5053365230560303, 'learning_rate': 8.210675931467674e-06, 'epoch': 0.3648, 'num_input_tokens_seen': 1912602615, 'completed': '36.48% (456 / 1_250)', 'remaining time': '7:39:53', 'throughput': '118767.82', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:12:10,160 >> {'loss': 1.7547, 'grad_norm': 0.5131360292434692, 'learning_rate': 8.200634707659231e-06, 'epoch': 0.3656, 'num_input_tokens_seen': 1916796919, 'completed': '36.56% (457 / 1_250)', 'remaining time': '7:39:19', 'throughput': '118263.74', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:12:45,428 >> {'loss': 1.5649, 'grad_norm': 0.2399134486913681, 'learning_rate': 8.190572423758836e-06, 'epoch': 0.3664, 'num_input_tokens_seen': 1920991223, 'completed': '36.64% (458 / 1_250)', 'remaining time': '7:38:45', 'throughput': '118928.86', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:13:20,787 >> {'loss': 1.706, 'grad_norm': 0.49584272503852844, 'learning_rate': 8.180489158234202e-06, 'epoch': 0.3672, 'num_input_tokens_seen': 1925185527, 'completed': '36.72% (459 / 1_250)', 'remaining time': '7:38:11', 'throughput': '118620.52', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:13:56,220 >> {'loss': 1.6212, 'grad_norm': 0.5153130292892456, 'learning_rate': 8.170384989716657e-06, 'epoch': 0.368, 'num_input_tokens_seen': 1929379831, 'completed': '36.80% (460 / 1_250)', 'remaining time': '7:37:38', 'throughput': '118371.08', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:14:28,031 >> {'loss': 1.78, 'grad_norm': 0.33255451917648315, 'learning_rate': 8.16025999700054e-06, 'epoch': 0.3688, 'num_input_tokens_seen': 1933574135, 'completed': '36.88% (461 / 1_250)', 'remaining time': '7:36:58', 'throughput': '131849.51', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:15:02,091 >> {'loss': 1.6545, 'grad_norm': 0.400464802980423, 'learning_rate': 8.150114259042574e-06, 'epoch': 0.3696, 'num_input_tokens_seen': 1937768439, 'completed': '36.96% (462 / 1_250)', 'remaining time': '7:36:22', 'throughput': '123144.44', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:15:33,795 >> {'loss': 1.5485, 'grad_norm': 0.43470966815948486, 'learning_rate': 8.139947854961267e-06, 'epoch': 0.3704, 'num_input_tokens_seen': 1941962743, 'completed': '37.04% (463 / 1_250)', 'remaining time': '7:35:42', 'throughput': '132297.92', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:16:06,837 >> {'loss': 1.4643, 'grad_norm': 0.3734474778175354, 'learning_rate': 8.129760864036275e-06, 'epoch': 0.3712, 'num_input_tokens_seen': 1946157047, 'completed': '37.12% (464 / 1_250)', 'remaining time': '7:35:05', 'throughput': '126939.64', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:16:42,250 >> {'loss': 1.7341, 'grad_norm': 0.44572076201438904, 'learning_rate': 8.119553365707802e-06, 'epoch': 0.372, 'num_input_tokens_seen': 1950351351, 'completed': '37.20% (465 / 1_250)', 'remaining time': '7:34:31', 'throughput': '118439.87', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:17:16,729 >> {'loss': 1.4663, 'grad_norm': 0.40696975588798523, 'learning_rate': 8.109325439575973e-06, 'epoch': 0.3728, 'num_input_tokens_seen': 1954545655, 'completed': '37.28% (466 / 1_250)', 'remaining time': '7:33:56', 'throughput': '121647.19', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:17:51,740 >> {'loss': 1.392, 'grad_norm': 0.3690614402294159, 'learning_rate': 8.099077165400204e-06, 'epoch': 0.3736, 'num_input_tokens_seen': 1958739959, 'completed': '37.36% (467 / 1_250)', 'remaining time': '7:33:22', 'throughput': '119797.65', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:18:25,870 >> {'loss': 1.678, 'grad_norm': 0.4379144608974457, 'learning_rate': 8.088808623098603e-06, 'epoch': 0.3744, 'num_input_tokens_seen': 1962934263, 'completed': '37.44% (468 / 1_250)', 'remaining time': '7:32:46', 'throughput': '122893.14', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:19:01,115 >> {'loss': 1.676, 'grad_norm': 0.24663594365119934, 'learning_rate': 8.07851989274732e-06, 'epoch': 0.3752, 'num_input_tokens_seen': 1967128567, 'completed': '37.52% (469 / 1_250)', 'remaining time': '7:32:12', 'throughput': '119006.00', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:19:36,610 >> {'loss': 1.6625, 'grad_norm': 0.2584947347640991, 'learning_rate': 8.068211054579944e-06, 'epoch': 0.376, 'num_input_tokens_seen': 1971322871, 'completed': '37.60% (470 / 1_250)', 'remaining time': '7:31:38', 'throughput': '118164.49', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:20:11,566 >> {'loss': 1.5317, 'grad_norm': 0.2658149003982544, 'learning_rate': 8.057882188986864e-06, 'epoch': 0.3768, 'num_input_tokens_seen': 1975517175, 'completed': '37.68% (471 / 1_250)', 'remaining time': '7:31:04', 'throughput': '119987.67', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:20:46,735 >> {'loss': 1.5218, 'grad_norm': 0.24804067611694336, 'learning_rate': 8.04753337651465e-06, 'epoch': 0.3776, 'num_input_tokens_seen': 1979711479, 'completed': '37.76% (472 / 1_250)', 'remaining time': '7:30:30', 'throughput': '119261.26', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:21:21,592 >> {'loss': 1.5406, 'grad_norm': 0.5341883301734924, 'learning_rate': 8.03716469786542e-06, 'epoch': 0.3784, 'num_input_tokens_seen': 1983905783, 'completed': '37.84% (473 / 1_250)', 'remaining time': '7:29:55', 'throughput': '120328.42', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:21:56,776 >> {'loss': 1.8724, 'grad_norm': 0.41645634174346924, 'learning_rate': 8.026776233896216e-06, 'epoch': 0.3792, 'num_input_tokens_seen': 1988100087, 'completed': '37.92% (474 / 1_250)', 'remaining time': '7:29:21', 'throughput': '119211.92', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:22:30,813 >> {'loss': 1.7023, 'grad_norm': 0.417762815952301, 'learning_rate': 8.016368065618361e-06, 'epoch': 0.38, 'num_input_tokens_seen': 1992294391, 'completed': '38.00% (475 / 1_250)', 'remaining time': '7:28:45', 'throughput': '123227.63', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:23:06,295 >> {'loss': 1.557, 'grad_norm': 0.5115085244178772, 'learning_rate': 8.005940274196847e-06, 'epoch': 0.3808, 'num_input_tokens_seen': 1996488695, 'completed': '38.08% (476 / 1_250)', 'remaining time': '7:28:12', 'throughput': '118208.06', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:23:41,743 >> {'loss': 1.8068, 'grad_norm': 0.31202560663223267, 'learning_rate': 7.995492940949683e-06, 'epoch': 0.3816, 'num_input_tokens_seen': 2000682999, 'completed': '38.16% (477 / 1_250)', 'remaining time': '7:27:38', 'throughput': '118323.25', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:24:17,103 >> {'loss': 1.6432, 'grad_norm': 0.386732816696167, 'learning_rate': 7.985026147347275e-06, 'epoch': 0.3824, 'num_input_tokens_seen': 2004877303, 'completed': '38.24% (478 / 1_250)', 'remaining time': '7:27:05', 'throughput': '118617.63', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:24:48,852 >> {'loss': 1.4999, 'grad_norm': 0.23795253038406372, 'learning_rate': 7.97453997501178e-06, 'epoch': 0.3832, 'num_input_tokens_seen': 2009071607, 'completed': '38.32% (479 / 1_250)', 'remaining time': '7:26:25', 'throughput': '132109.79', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:25:24,292 >> {'loss': 1.5301, 'grad_norm': 0.3191041350364685, 'learning_rate': 7.964034505716478e-06, 'epoch': 0.384, 'num_input_tokens_seen': 2013265911, 'completed': '38.40% (480 / 1_250)', 'remaining time': '7:25:51', 'throughput': '118349.26', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:25:59,980 >> {'loss': 1.4764, 'grad_norm': 0.2484116107225418, 'learning_rate': 7.953509821385126e-06, 'epoch': 0.3848, 'num_input_tokens_seen': 2017460215, 'completed': '38.48% (481 / 1_250)', 'remaining time': '7:25:18', 'throughput': '117526.77', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:26:35,213 >> {'loss': 1.4671, 'grad_norm': 0.2458764761686325, 'learning_rate': 7.94296600409133e-06, 'epoch': 0.3856, 'num_input_tokens_seen': 2021654519, 'completed': '38.56% (482 / 1_250)', 'remaining time': '7:24:44', 'throughput': '119044.59', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:27:06,012 >> {'loss': 1.6615, 'grad_norm': 0.32683107256889343, 'learning_rate': 7.932403136057893e-06, 'epoch': 0.3864, 'num_input_tokens_seen': 2025848823, 'completed': '38.64% (483 / 1_250)', 'remaining time': '7:24:03', 'throughput': '136184.57', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:27:41,427 >> {'loss': 1.5035, 'grad_norm': 0.4057336747646332, 'learning_rate': 7.921821299656182e-06, 'epoch': 0.3872, 'num_input_tokens_seen': 2030043127, 'completed': '38.72% (484 / 1_250)', 'remaining time': '7:23:29', 'throughput': '118432.08', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:28:16,861 >> {'loss': 1.512, 'grad_norm': 0.5038105249404907, 'learning_rate': 7.911220577405485e-06, 'epoch': 0.388, 'num_input_tokens_seen': 2034237431, 'completed': '38.80% (485 / 1_250)', 'remaining time': '7:22:56', 'throughput': '118368.09', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:28:52,256 >> {'loss': 1.7775, 'grad_norm': 0.6948778629302979, 'learning_rate': 7.900601051972362e-06, 'epoch': 0.3888, 'num_input_tokens_seen': 2038431735, 'completed': '38.88% (486 / 1_250)', 'remaining time': '7:22:22', 'throughput': '118500.50', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:29:26,279 >> {'loss': 1.6467, 'grad_norm': 0.3934985101222992, 'learning_rate': 7.889962806170004e-06, 'epoch': 0.3896, 'num_input_tokens_seen': 2042626039, 'completed': '38.96% (487 / 1_250)', 'remaining time': '7:21:46', 'throughput': '123279.97', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:30:01,371 >> {'loss': 1.4687, 'grad_norm': 0.28087323904037476, 'learning_rate': 7.879305922957594e-06, 'epoch': 0.3904, 'num_input_tokens_seen': 2046820343, 'completed': '39.04% (488 / 1_250)', 'remaining time': '7:21:12', 'throughput': '119521.00', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:30:36,663 >> {'loss': 1.6049, 'grad_norm': 0.5010564923286438, 'learning_rate': 7.86863048543964e-06, 'epoch': 0.3912, 'num_input_tokens_seen': 2051014646, 'completed': '39.12% (489 / 1_250)', 'remaining time': '7:20:38', 'throughput': '118846.46', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:31:10,981 >> {'loss': 1.9531, 'grad_norm': 0.3657705783843994, 'learning_rate': 7.857936576865356e-06, 'epoch': 0.392, 'num_input_tokens_seen': 2055208950, 'completed': '39.20% (490 / 1_250)', 'remaining time': '7:20:03', 'throughput': '122219.07', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:31:46,351 >> {'loss': 1.5383, 'grad_norm': 0.825958788394928, 'learning_rate': 7.847224280627986e-06, 'epoch': 0.3928, 'num_input_tokens_seen': 2059403254, 'completed': '39.28% (491 / 1_250)', 'remaining time': '7:19:29', 'throughput': '118583.46', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:32:16,934 >> {'loss': 1.5605, 'grad_norm': 0.32378891110420227, 'learning_rate': 7.836493680264167e-06, 'epoch': 0.3936, 'num_input_tokens_seen': 2063597558, 'completed': '39.36% (492 / 1_250)', 'remaining time': '7:18:48', 'throughput': '137143.87', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:32:52,463 >> {'loss': 1.581, 'grad_norm': 0.5265981554985046, 'learning_rate': 7.825744859453277e-06, 'epoch': 0.3944, 'num_input_tokens_seen': 2067791862, 'completed': '39.44% (493 / 1_250)', 'remaining time': '7:18:14', 'throughput': '118055.23', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:33:27,737 >> {'loss': 1.7223, 'grad_norm': 0.7678369879722595, 'learning_rate': 7.814977902016779e-06, 'epoch': 0.3952, 'num_input_tokens_seen': 2071986166, 'completed': '39.52% (494 / 1_250)', 'remaining time': '7:17:40', 'throughput': '118906.23', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:34:03,325 >> {'loss': 1.532, 'grad_norm': 0.26027417182922363, 'learning_rate': 7.804192891917572e-06, 'epoch': 0.396, 'num_input_tokens_seen': 2076180470, 'completed': '39.60% (495 / 1_250)', 'remaining time': '7:17:07', 'throughput': '117855.10', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:34:38,599 >> {'loss': 1.8491, 'grad_norm': 0.9035544991493225, 'learning_rate': 7.79338991325933e-06, 'epoch': 0.3968, 'num_input_tokens_seen': 2080374774, 'completed': '39.68% (496 / 1_250)', 'remaining time': '7:16:33', 'throughput': '118905.95', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:35:13,083 >> {'loss': 1.519, 'grad_norm': 0.6365873217582703, 'learning_rate': 7.782569050285852e-06, 'epoch': 0.3976, 'num_input_tokens_seen': 2084569078, 'completed': '39.76% (497 / 1_250)', 'remaining time': '7:15:58', 'throughput': '121633.52', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:35:48,542 >> {'loss': 1.696, 'grad_norm': 0.5732784271240234, 'learning_rate': 7.771730387380399e-06, 'epoch': 0.3984, 'num_input_tokens_seen': 2088763382, 'completed': '39.84% (498 / 1_250)', 'remaining time': '7:15:24', 'throughput': '118283.30', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:36:23,675 >> {'loss': 1.6699, 'grad_norm': 0.6758745312690735, 'learning_rate': 7.760874009065041e-06, 'epoch': 0.3992, 'num_input_tokens_seen': 2092957686, 'completed': '39.92% (499 / 1_250)', 'remaining time': '7:14:50', 'throughput': '119384.57', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:36:55,458 >> {'loss': 1.6244, 'grad_norm': 0.4661315381526947, 'learning_rate': 7.75e-06, 'epoch': 0.4, 'num_input_tokens_seen': 2097151990, 'completed': '40.00% (500 / 1_250)', 'remaining time': '7:14:11', 'throughput': '131968.00', 'gpu_mem_free': '16314MB'} +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:689: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +[INFO|trainer.py:3503] 2026-05-02 06:37:03,474 >> Saving model checkpoint to /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-500 +[INFO|configuration_utils.py:472] 2026-05-02 06:37:03,475 >> Configuration saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-500/config.json +[INFO|configuration_utils.py:807] 2026-05-02 06:37:03,476 >> Configuration saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-500/generation_config.json +[INFO|modeling_utils.py:2807] 2026-05-02 06:37:15,244 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 3 checkpoint shards. You can find where each parameters has been saved in the index located at /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-500/model.safetensors.index.json. +[INFO|tokenization_utils_base.py:2684] 2026-05-02 06:37:15,246 >> tokenizer config file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-500/tokenizer_config.json +[INFO|tokenization_utils_base.py:2693] 2026-05-02 06:37:15,246 >> Special tokens file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-500/special_tokens_map.json +[INFO|tokenization_utils_base.py:2684] 2026-05-02 06:37:23,692 >> tokenizer config file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/tokenizer_config.json +[INFO|tokenization_utils_base.py:2693] 2026-05-02 06:37:23,693 >> Special tokens file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/special_tokens_map.json +[INFO|trainer.py:3595] 2026-05-02 06:37:23,697 >> Deleting older checkpoint [/tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-375] due to args.save_total_limit +[WARNING|trainer.py:870] 2026-05-02 06:37:24,802 >> Save streaming dataset state: {'epoch': 0, 'sample_in_epoch': 128000, 'num_canonical_nodes': 2, 'shuffle_seed': 42, 'initial_physical_nodes': 2} +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/utils/checkpoint.py:1399: FutureWarning: `torch.cpu.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cpu', args...)` instead. + with device_autocast_ctx, torch.cpu.amp.autocast(**cpu_autocast_kwargs), recompute_context: # type: ignore[attr-defined] +[INFO|trainer.py:175] 2026-05-02 06:38:00,021 >> {'loss': 1.5074, 'grad_norm': 0.4743976891040802, 'learning_rate': 7.739108444982982e-06, 'epoch': 0.4008, 'num_input_tokens_seen': 2101346294, 'completed': '40.08% (501 / 1_250)', 'remaining time': '7:14:21', 'throughput': '64964.86', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:38:35,526 >> {'loss': 1.7594, 'grad_norm': 0.7432764768600464, 'learning_rate': 7.72819942894852e-06, 'epoch': 0.4016, 'num_input_tokens_seen': 2105540598, 'completed': '40.16% (502 / 1_250)', 'remaining time': '7:13:47', 'throughput': '118132.51', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:39:10,911 >> {'loss': 1.6005, 'grad_norm': 0.7193065881729126, 'learning_rate': 7.717273036967312e-06, 'epoch': 0.4024, 'num_input_tokens_seen': 2109734902, 'completed': '40.24% (503 / 1_250)', 'remaining time': '7:13:13', 'throughput': '118530.29', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:39:46,220 >> {'loss': 1.5864, 'grad_norm': 0.6297187209129333, 'learning_rate': 7.70632935424556e-06, 'epoch': 0.4032, 'num_input_tokens_seen': 2113929205, 'completed': '40.32% (504 / 1_250)', 'remaining time': '7:12:39', 'throughput': '118788.53', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:40:21,653 >> {'loss': 1.5066, 'grad_norm': 0.5733551383018494, 'learning_rate': 7.695368466124298e-06, 'epoch': 0.404, 'num_input_tokens_seen': 2118123509, 'completed': '40.40% (505 / 1_250)', 'remaining time': '7:12:05', 'throughput': '118374.00', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:40:56,765 >> {'loss': 1.4573, 'grad_norm': 0.43998709321022034, 'learning_rate': 7.684390458078733e-06, 'epoch': 0.4048, 'num_input_tokens_seen': 2122317813, 'completed': '40.48% (506 / 1_250)', 'remaining time': '7:11:31', 'throughput': '119456.36', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:41:31,936 >> {'loss': 1.5353, 'grad_norm': 0.33583730459213257, 'learning_rate': 7.673395415717578e-06, 'epoch': 0.4056, 'num_input_tokens_seen': 2126512116, 'completed': '40.56% (507 / 1_250)', 'remaining time': '7:10:57', 'throughput': '119254.98', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:42:05,737 >> {'loss': 1.5097, 'grad_norm': 0.5071771144866943, 'learning_rate': 7.662383424782383e-06, 'epoch': 0.4064, 'num_input_tokens_seen': 2130706420, 'completed': '40.64% (508 / 1_250)', 'remaining time': '7:10:20', 'throughput': '124087.18', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:42:40,929 >> {'loss': 1.6303, 'grad_norm': 0.3004322052001953, 'learning_rate': 7.651354571146866e-06, 'epoch': 0.4072, 'num_input_tokens_seen': 2134900724, 'completed': '40.72% (509 / 1_250)', 'remaining time': '7:09:46', 'throughput': '119184.41', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:43:16,406 >> {'loss': 1.4483, 'grad_norm': 0.42576864361763, 'learning_rate': 7.64030894081624e-06, 'epoch': 0.408, 'num_input_tokens_seen': 2139095028, 'completed': '40.80% (510 / 1_250)', 'remaining time': '7:09:12', 'throughput': '118224.41', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:43:51,802 >> {'loss': 1.6017, 'grad_norm': 0.36974185705184937, 'learning_rate': 7.62924661992655e-06, 'epoch': 0.4088, 'num_input_tokens_seen': 2143289332, 'completed': '40.88% (511 / 1_250)', 'remaining time': '7:08:38', 'throughput': '118495.87', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:44:27,249 >> {'loss': 1.491, 'grad_norm': 0.26450103521347046, 'learning_rate': 7.618167694743998e-06, 'epoch': 0.4096, 'num_input_tokens_seen': 2147483636, 'completed': '40.96% (512 / 1_250)', 'remaining time': '7:08:05', 'throughput': '118325.98', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:45:02,424 >> {'loss': 1.5601, 'grad_norm': 0.7092283964157104, 'learning_rate': 7.607072251664266e-06, 'epoch': 0.4104, 'num_input_tokens_seen': 2151677940, 'completed': '41.04% (513 / 1_250)', 'remaining time': '7:07:30', 'throughput': '119240.51', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:45:37,825 >> {'loss': 1.702, 'grad_norm': 0.7385356426239014, 'learning_rate': 7.595960377211849e-06, 'epoch': 0.4112, 'num_input_tokens_seen': 2155872244, 'completed': '41.12% (514 / 1_250)', 'remaining time': '7:06:56', 'throughput': '118480.05', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:46:12,112 >> {'loss': 1.6843, 'grad_norm': 0.4230199158191681, 'learning_rate': 7.584832158039379e-06, 'epoch': 0.412, 'num_input_tokens_seen': 2160066548, 'completed': '41.20% (515 / 1_250)', 'remaining time': '7:06:21', 'throughput': '122331.00', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:46:46,806 >> {'loss': 1.4725, 'grad_norm': 0.3520364463329315, 'learning_rate': 7.57368768092694e-06, 'epoch': 0.4128, 'num_input_tokens_seen': 2164260852, 'completed': '41.28% (516 / 1_250)', 'remaining time': '7:05:46', 'throughput': '120895.28', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:47:21,583 >> {'loss': 1.6144, 'grad_norm': 0.5796244144439697, 'learning_rate': 7.562527032781405e-06, 'epoch': 0.4136, 'num_input_tokens_seen': 2168455156, 'completed': '41.36% (517 / 1_250)', 'remaining time': '7:05:11', 'throughput': '120605.09', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:47:56,848 >> {'loss': 1.6375, 'grad_norm': 0.46054691076278687, 'learning_rate': 7.5513503006357515e-06, 'epoch': 0.4144, 'num_input_tokens_seen': 2172649460, 'completed': '41.44% (518 / 1_250)', 'remaining time': '7:04:37', 'throughput': '118934.97', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:48:31,091 >> {'loss': 1.6965, 'grad_norm': 0.5259132981300354, 'learning_rate': 7.540157571648379e-06, 'epoch': 0.4152, 'num_input_tokens_seen': 2176843764, 'completed': '41.52% (519 / 1_250)', 'remaining time': '7:04:01', 'throughput': '122485.99', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:49:06,407 >> {'loss': 1.5628, 'grad_norm': 0.32385408878326416, 'learning_rate': 7.528948933102439e-06, 'epoch': 0.416, 'num_input_tokens_seen': 2181038067, 'completed': '41.60% (520 / 1_250)', 'remaining time': '7:03:27', 'throughput': '118766.53', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:49:37,293 >> {'loss': 1.7525, 'grad_norm': 0.4338981807231903, 'learning_rate': 7.517724472405147e-06, 'epoch': 0.4168, 'num_input_tokens_seen': 2185232371, 'completed': '41.68% (521 / 1_250)', 'remaining time': '7:02:47', 'throughput': '135797.61', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:50:11,817 >> {'loss': 1.5995, 'grad_norm': 0.3343155086040497, 'learning_rate': 7.506484277087099e-06, 'epoch': 0.4176, 'num_input_tokens_seen': 2189426675, 'completed': '41.76% (522 / 1_250)', 'remaining time': '7:02:12', 'throughput': '121490.68', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:50:46,746 >> {'loss': 1.5203, 'grad_norm': 0.3057946264743805, 'learning_rate': 7.495228434801597e-06, 'epoch': 0.4184, 'num_input_tokens_seen': 2193620979, 'completed': '41.84% (523 / 1_250)', 'remaining time': '7:01:37', 'throughput': '120081.75', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:51:22,246 >> {'loss': 1.5934, 'grad_norm': 0.42513608932495117, 'learning_rate': 7.483957033323964e-06, 'epoch': 0.4192, 'num_input_tokens_seen': 2197815283, 'completed': '41.92% (524 / 1_250)', 'remaining time': '7:01:03', 'throughput': '118148.60', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:51:57,747 >> {'loss': 1.5617, 'grad_norm': 0.3588137626647949, 'learning_rate': 7.472670160550849e-06, 'epoch': 0.42, 'num_input_tokens_seen': 2202009587, 'completed': '42.00% (525 / 1_250)', 'remaining time': '7:00:29', 'throughput': '118146.60', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:52:33,098 >> {'loss': 1.7115, 'grad_norm': 0.971703052520752, 'learning_rate': 7.461367904499554e-06, 'epoch': 0.4208, 'num_input_tokens_seen': 2206203891, 'completed': '42.08% (526 / 1_250)', 'remaining time': '6:59:55', 'throughput': '118648.43', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:53:03,760 >> {'loss': 1.7269, 'grad_norm': 0.6083213090896606, 'learning_rate': 7.450050353307343e-06, 'epoch': 0.4216, 'num_input_tokens_seen': 2210398195, 'completed': '42.16% (527 / 1_250)', 'remaining time': '6:59:15', 'throughput': '136787.60', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:53:39,019 >> {'loss': 1.5802, 'grad_norm': 0.5760592818260193, 'learning_rate': 7.438717595230753e-06, 'epoch': 0.4224, 'num_input_tokens_seen': 2214592499, 'completed': '42.24% (528 / 1_250)', 'remaining time': '6:58:41', 'throughput': '118958.34', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:54:14,431 >> {'loss': 1.5842, 'grad_norm': 0.5874526500701904, 'learning_rate': 7.427369718644907e-06, 'epoch': 0.4232, 'num_input_tokens_seen': 2218786803, 'completed': '42.32% (529 / 1_250)', 'remaining time': '6:58:07', 'throughput': '118443.81', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:54:49,244 >> {'loss': 1.5247, 'grad_norm': 0.42759400606155396, 'learning_rate': 7.416006812042827e-06, 'epoch': 0.424, 'num_input_tokens_seen': 2222981107, 'completed': '42.40% (530 / 1_250)', 'remaining time': '6:57:32', 'throughput': '120479.62', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:55:24,462 >> {'loss': 1.6482, 'grad_norm': 0.5132678151130676, 'learning_rate': 7.4046289640347434e-06, 'epoch': 0.4248, 'num_input_tokens_seen': 2227175411, 'completed': '42.48% (531 / 1_250)', 'remaining time': '6:56:58', 'throughput': '119097.65', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:55:59,704 >> {'loss': 1.5634, 'grad_norm': 0.29016080498695374, 'learning_rate': 7.393236263347398e-06, 'epoch': 0.4256, 'num_input_tokens_seen': 2231369715, 'completed': '42.56% (532 / 1_250)', 'remaining time': '6:56:24', 'throughput': '119014.16', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:56:33,731 >> {'loss': 1.6076, 'grad_norm': 0.3291662335395813, 'learning_rate': 7.3818287988233565e-06, 'epoch': 0.4264, 'num_input_tokens_seen': 2235564019, 'completed': '42.64% (533 / 1_250)', 'remaining time': '6:55:48', 'throughput': '123261.13', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:57:09,232 >> {'loss': 1.6208, 'grad_norm': 0.42017221450805664, 'learning_rate': 7.370406659420326e-06, 'epoch': 0.4272, 'num_input_tokens_seen': 2239758323, 'completed': '42.72% (534 / 1_250)', 'remaining time': '6:55:14', 'throughput': '118147.17', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:57:44,694 >> {'loss': 1.4142, 'grad_norm': 0.49731600284576416, 'learning_rate': 7.358969934210439e-06, 'epoch': 0.428, 'num_input_tokens_seen': 2243952626, 'completed': '42.80% (535 / 1_250)', 'remaining time': '6:54:40', 'throughput': '118275.92', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:58:20,158 >> {'loss': 1.5776, 'grad_norm': 0.30672916769981384, 'learning_rate': 7.347518712379576e-06, 'epoch': 0.4288, 'num_input_tokens_seen': 2248146930, 'completed': '42.88% (536 / 1_250)', 'remaining time': '6:54:06', 'throughput': '118270.26', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:58:51,438 >> {'loss': 1.6133, 'grad_norm': 0.5745459198951721, 'learning_rate': 7.336053083226669e-06, 'epoch': 0.4296, 'num_input_tokens_seen': 2252341234, 'completed': '42.96% (537 / 1_250)', 'remaining time': '6:53:27', 'throughput': '134087.67', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:59:23,749 >> {'loss': 1.6655, 'grad_norm': 0.3062099814414978, 'learning_rate': 7.324573136162992e-06, 'epoch': 0.4304, 'num_input_tokens_seen': 2256535538, 'completed': '43.04% (538 / 1_250)', 'remaining time': '6:52:49', 'throughput': '129810.74', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 06:59:55,475 >> {'loss': 1.4798, 'grad_norm': 0.3205117881298065, 'learning_rate': 7.3130789607114825e-06, 'epoch': 0.4312, 'num_input_tokens_seen': 2260729842, 'completed': '43.12% (539 / 1_250)', 'remaining time': '6:52:10', 'throughput': '132203.04', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:00:30,677 >> {'loss': 1.5623, 'grad_norm': 0.5491670966148376, 'learning_rate': 7.301570646506029e-06, 'epoch': 0.432, 'num_input_tokens_seen': 2264924146, 'completed': '43.20% (540 / 1_250)', 'remaining time': '6:51:36', 'throughput': '119150.13', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:01:05,811 >> {'loss': 1.6197, 'grad_norm': 0.43046268820762634, 'learning_rate': 7.290048283290775e-06, 'epoch': 0.4328, 'num_input_tokens_seen': 2269118450, 'completed': '43.28% (541 / 1_250)', 'remaining time': '6:51:01', 'throughput': '119379.55', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:01:36,658 >> {'loss': 1.4301, 'grad_norm': 0.35520076751708984, 'learning_rate': 7.2785119609194255e-06, 'epoch': 0.4336, 'num_input_tokens_seen': 2273312754, 'completed': '43.36% (542 / 1_250)', 'remaining time': '6:50:21', 'throughput': '135973.85', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:02:11,925 >> {'loss': 1.6877, 'grad_norm': 0.26227039098739624, 'learning_rate': 7.266961769354538e-06, 'epoch': 0.4344, 'num_input_tokens_seen': 2277507058, 'completed': '43.44% (543 / 1_250)', 'remaining time': '6:49:47', 'throughput': '118928.29', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:02:47,326 >> {'loss': 1.5989, 'grad_norm': 0.31737029552459717, 'learning_rate': 7.255397798666829e-06, 'epoch': 0.4352, 'num_input_tokens_seen': 2281701362, 'completed': '43.52% (544 / 1_250)', 'remaining time': '6:49:13', 'throughput': '118480.95', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:03:22,715 >> {'loss': 1.5928, 'grad_norm': 0.2543856203556061, 'learning_rate': 7.243820139034464e-06, 'epoch': 0.436, 'num_input_tokens_seen': 2285895666, 'completed': '43.60% (545 / 1_250)', 'remaining time': '6:48:39', 'throughput': '118519.45', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:03:58,039 >> {'loss': 1.738, 'grad_norm': 0.4679945707321167, 'learning_rate': 7.232228880742358e-06, 'epoch': 0.4368, 'num_input_tokens_seen': 2290089970, 'completed': '43.68% (546 / 1_250)', 'remaining time': '6:48:05', 'throughput': '118737.99', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:04:32,020 >> {'loss': 1.5909, 'grad_norm': 0.26386386156082153, 'learning_rate': 7.220624114181472e-06, 'epoch': 0.4376, 'num_input_tokens_seen': 2294284274, 'completed': '43.76% (547 / 1_250)', 'remaining time': '6:47:29', 'throughput': '123431.54', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:05:07,091 >> {'loss': 1.7288, 'grad_norm': 0.28829771280288696, 'learning_rate': 7.209005929848107e-06, 'epoch': 0.4384, 'num_input_tokens_seen': 2298478578, 'completed': '43.84% (548 / 1_250)', 'remaining time': '6:46:55', 'throughput': '119595.84', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:05:42,279 >> {'loss': 1.7134, 'grad_norm': 0.3187029957771301, 'learning_rate': 7.197374418343196e-06, 'epoch': 0.4392, 'num_input_tokens_seen': 2302672882, 'completed': '43.92% (549 / 1_250)', 'remaining time': '6:46:21', 'throughput': '119194.46', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:06:17,773 >> {'loss': 1.7118, 'grad_norm': 0.6404929757118225, 'learning_rate': 7.185729670371605e-06, 'epoch': 0.44, 'num_input_tokens_seen': 2306867186, 'completed': '44.00% (550 / 1_250)', 'remaining time': '6:45:47', 'throughput': '118169.66', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:06:52,679 >> {'loss': 1.6035, 'grad_norm': 0.26612669229507446, 'learning_rate': 7.174071776741417e-06, 'epoch': 0.4408, 'num_input_tokens_seen': 2311061490, 'completed': '44.08% (551 / 1_250)', 'remaining time': '6:45:12', 'throughput': '120159.43', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:07:28,121 >> {'loss': 1.7034, 'grad_norm': 0.5007754564285278, 'learning_rate': 7.162400828363228e-06, 'epoch': 0.4416, 'num_input_tokens_seen': 2315255794, 'completed': '44.16% (552 / 1_250)', 'remaining time': '6:44:38', 'throughput': '118345.25', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:08:03,474 >> {'loss': 1.7556, 'grad_norm': 0.4209626019001007, 'learning_rate': 7.150716916249439e-06, 'epoch': 0.4424, 'num_input_tokens_seen': 2319450098, 'completed': '44.24% (553 / 1_250)', 'remaining time': '6:44:04', 'throughput': '118637.83', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:08:38,591 >> {'loss': 1.548, 'grad_norm': 0.3188875615596771, 'learning_rate': 7.139020131513543e-06, 'epoch': 0.4432, 'num_input_tokens_seen': 2323644402, 'completed': '44.32% (554 / 1_250)', 'remaining time': '6:43:30', 'throughput': '119440.71', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:09:14,026 >> {'loss': 1.6488, 'grad_norm': 0.3763778805732727, 'learning_rate': 7.127310565369415e-06, 'epoch': 0.444, 'num_input_tokens_seen': 2327838706, 'completed': '44.40% (555 / 1_250)', 'remaining time': '6:42:56', 'throughput': '118366.16', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:09:49,326 >> {'loss': 1.6064, 'grad_norm': 0.31193673610687256, 'learning_rate': 7.115588309130609e-06, 'epoch': 0.4448, 'num_input_tokens_seen': 2332033010, 'completed': '44.48% (556 / 1_250)', 'remaining time': '6:42:22', 'throughput': '118816.92', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:10:24,712 >> {'loss': 1.7701, 'grad_norm': 0.2931908965110779, 'learning_rate': 7.103853454209629e-06, 'epoch': 0.4456, 'num_input_tokens_seen': 2336227314, 'completed': '44.56% (557 / 1_250)', 'remaining time': '6:41:48', 'throughput': '118530.14', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:10:57,411 >> {'loss': 1.5622, 'grad_norm': 0.22227391600608826, 'learning_rate': 7.092106092117233e-06, 'epoch': 0.4464, 'num_input_tokens_seen': 2340421618, 'completed': '44.64% (558 / 1_250)', 'remaining time': '6:41:10', 'throughput': '128270.30', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:11:32,695 >> {'loss': 1.4791, 'grad_norm': 0.20100893080234528, 'learning_rate': 7.08034631446171e-06, 'epoch': 0.4472, 'num_input_tokens_seen': 2344615922, 'completed': '44.72% (559 / 1_250)', 'remaining time': '6:40:36', 'throughput': '118873.38', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:12:07,041 >> {'loss': 1.5514, 'grad_norm': 0.29321038722991943, 'learning_rate': 7.068574212948169e-06, 'epoch': 0.448, 'num_input_tokens_seen': 2348810226, 'completed': '44.80% (560 / 1_250)', 'remaining time': '6:40:01', 'throughput': '122120.14', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:12:42,279 >> {'loss': 1.64, 'grad_norm': 0.2781587243080139, 'learning_rate': 7.056789879377823e-06, 'epoch': 0.4488, 'num_input_tokens_seen': 2353004530, 'completed': '44.88% (561 / 1_250)', 'remaining time': '6:39:26', 'throughput': '119026.79', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:13:17,702 >> {'loss': 1.7254, 'grad_norm': 0.38674497604370117, 'learning_rate': 7.044993405647269e-06, 'epoch': 0.4496, 'num_input_tokens_seen': 2357198834, 'completed': '44.96% (562 / 1_250)', 'remaining time': '6:38:52', 'throughput': '118406.38', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:13:52,930 >> {'loss': 1.7195, 'grad_norm': 0.3436574935913086, 'learning_rate': 7.033184883747784e-06, 'epoch': 0.4504, 'num_input_tokens_seen': 2361393138, 'completed': '45.04% (563 / 1_250)', 'remaining time': '6:38:18', 'throughput': '119062.54', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:14:28,110 >> {'loss': 1.6665, 'grad_norm': 0.5056725144386292, 'learning_rate': 7.021364405764588e-06, 'epoch': 0.4512, 'num_input_tokens_seen': 2365587442, 'completed': '45.12% (564 / 1_250)', 'remaining time': '6:37:44', 'throughput': '119221.90', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:14:59,536 >> {'loss': 1.709, 'grad_norm': 0.26701945066452026, 'learning_rate': 7.009532063876149e-06, 'epoch': 0.452, 'num_input_tokens_seen': 2369781746, 'completed': '45.20% (565 / 1_250)', 'remaining time': '6:37:05', 'throughput': '133465.71', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:15:34,804 >> {'loss': 1.6394, 'grad_norm': 0.41413652896881104, 'learning_rate': 6.99768795035344e-06, 'epoch': 0.4528, 'num_input_tokens_seen': 2373976050, 'completed': '45.28% (566 / 1_250)', 'remaining time': '6:36:31', 'throughput': '118929.56', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:16:07,191 >> {'loss': 1.6591, 'grad_norm': 0.37054964900016785, 'learning_rate': 6.985832157559241e-06, 'epoch': 0.4536, 'num_input_tokens_seen': 2378170353, 'completed': '45.36% (567 / 1_250)', 'remaining time': '6:35:53', 'throughput': '129503.02', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:16:42,650 >> {'loss': 1.538, 'grad_norm': 0.22614850103855133, 'learning_rate': 6.9739647779474064e-06, 'epoch': 0.4544, 'num_input_tokens_seen': 2382364657, 'completed': '45.44% (568 / 1_250)', 'remaining time': '6:35:19', 'throughput': '118288.29', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:17:17,561 >> {'loss': 1.6715, 'grad_norm': 1.5458465814590454, 'learning_rate': 6.962085904062145e-06, 'epoch': 0.4552, 'num_input_tokens_seen': 2386558961, 'completed': '45.52% (569 / 1_250)', 'remaining time': '6:34:45', 'throughput': '120140.44', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:17:53,094 >> {'loss': 1.5584, 'grad_norm': 0.36872783303260803, 'learning_rate': 6.950195628537301e-06, 'epoch': 0.456, 'num_input_tokens_seen': 2390753265, 'completed': '45.60% (570 / 1_250)', 'remaining time': '6:34:11', 'throughput': '118041.52', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:18:28,448 >> {'loss': 1.6266, 'grad_norm': 0.37249162793159485, 'learning_rate': 6.938294044095632e-06, 'epoch': 0.4568, 'num_input_tokens_seen': 2394947569, 'completed': '45.68% (571 / 1_250)', 'remaining time': '6:33:37', 'throughput': '118637.80', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:19:03,759 >> {'loss': 1.8134, 'grad_norm': 0.3916323184967041, 'learning_rate': 6.926381243548084e-06, 'epoch': 0.4576, 'num_input_tokens_seen': 2399141873, 'completed': '45.76% (572 / 1_250)', 'remaining time': '6:33:02', 'throughput': '118781.73', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:19:38,671 >> {'loss': 1.7166, 'grad_norm': 0.3803962171077728, 'learning_rate': 6.914457319793069e-06, 'epoch': 0.4584, 'num_input_tokens_seen': 2403336177, 'completed': '45.84% (573 / 1_250)', 'remaining time': '6:32:28', 'throughput': '120138.45', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:20:13,866 >> {'loss': 1.6176, 'grad_norm': 0.595801830291748, 'learning_rate': 6.902522365815738e-06, 'epoch': 0.4592, 'num_input_tokens_seen': 2407530481, 'completed': '45.92% (574 / 1_250)', 'remaining time': '6:31:54', 'throughput': '119171.96', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:20:45,465 >> {'loss': 1.4819, 'grad_norm': 0.2092677354812622, 'learning_rate': 6.890576474687264e-06, 'epoch': 0.46, 'num_input_tokens_seen': 2411724785, 'completed': '46.00% (575 / 1_250)', 'remaining time': '6:31:15', 'throughput': '132735.08', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:21:21,002 >> {'loss': 1.5677, 'grad_norm': 0.9458425045013428, 'learning_rate': 6.878619739564102e-06, 'epoch': 0.4608, 'num_input_tokens_seen': 2415919089, 'completed': '46.08% (576 / 1_250)', 'remaining time': '6:30:41', 'throughput': '118027.99', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:21:53,494 >> {'loss': 1.4654, 'grad_norm': 0.626928448677063, 'learning_rate': 6.866652253687275e-06, 'epoch': 0.4616, 'num_input_tokens_seen': 2420113393, 'completed': '46.16% (577 / 1_250)', 'remaining time': '6:30:04', 'throughput': '129087.68', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:22:28,960 >> {'loss': 1.3451, 'grad_norm': 0.23680607974529266, 'learning_rate': 6.8546741103816435e-06, 'epoch': 0.4624, 'num_input_tokens_seen': 2424307697, 'completed': '46.24% (578 / 1_250)', 'remaining time': '6:29:30', 'throughput': '118260.92', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:23:04,288 >> {'loss': 1.6042, 'grad_norm': 0.5466395020484924, 'learning_rate': 6.842685403055172e-06, 'epoch': 0.4632, 'num_input_tokens_seen': 2428502001, 'completed': '46.32% (579 / 1_250)', 'remaining time': '6:28:56', 'throughput': '118724.59', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:23:39,612 >> {'loss': 1.4822, 'grad_norm': 0.41078975796699524, 'learning_rate': 6.830686225198211e-06, 'epoch': 0.464, 'num_input_tokens_seen': 2432696305, 'completed': '46.40% (580 / 1_250)', 'remaining time': '6:28:21', 'throughput': '118737.32', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:24:15,045 >> {'loss': 1.6794, 'grad_norm': 7.239644527435303, 'learning_rate': 6.818676670382759e-06, 'epoch': 0.4648, 'num_input_tokens_seen': 2436890609, 'completed': '46.48% (581 / 1_250)', 'remaining time': '6:27:47', 'throughput': '118373.18', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:24:47,137 >> {'loss': 1.6041, 'grad_norm': 0.9345746636390686, 'learning_rate': 6.806656832261738e-06, 'epoch': 0.4656, 'num_input_tokens_seen': 2441084913, 'completed': '46.56% (582 / 1_250)', 'remaining time': '6:27:10', 'throughput': '130698.63', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:25:22,774 >> {'loss': 1.5824, 'grad_norm': 0.31346529722213745, 'learning_rate': 6.794626804568259e-06, 'epoch': 0.4664, 'num_input_tokens_seen': 2445279217, 'completed': '46.64% (583 / 1_250)', 'remaining time': '6:26:36', 'throughput': '117695.25', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:25:57,144 >> {'loss': 1.5204, 'grad_norm': 1.023280382156372, 'learning_rate': 6.782586681114894e-06, 'epoch': 0.4672, 'num_input_tokens_seen': 2449473521, 'completed': '46.72% (584 / 1_250)', 'remaining time': '6:26:00', 'throughput': '122031.67', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:26:32,086 >> {'loss': 1.5008, 'grad_norm': 0.5572710633277893, 'learning_rate': 6.770536555792945e-06, 'epoch': 0.468, 'num_input_tokens_seen': 2453667825, 'completed': '46.80% (585 / 1_250)', 'remaining time': '6:25:26', 'throughput': '120037.31', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:27:07,643 >> {'loss': 1.5506, 'grad_norm': 0.76396644115448, 'learning_rate': 6.758476522571711e-06, 'epoch': 0.4688, 'num_input_tokens_seen': 2457862129, 'completed': '46.88% (586 / 1_250)', 'remaining time': '6:24:52', 'throughput': '117960.66', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:27:42,900 >> {'loss': 1.7427, 'grad_norm': 0.6854556798934937, 'learning_rate': 6.7464066754977505e-06, 'epoch': 0.4696, 'num_input_tokens_seen': 2462056433, 'completed': '46.96% (587 / 1_250)', 'remaining time': '6:24:18', 'throughput': '118962.41', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:28:17,895 >> {'loss': 1.5426, 'grad_norm': 0.31526029109954834, 'learning_rate': 6.734327108694161e-06, 'epoch': 0.4704, 'num_input_tokens_seen': 2466250737, 'completed': '47.04% (588 / 1_250)', 'remaining time': '6:23:43', 'throughput': '119853.57', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:28:52,463 >> {'loss': 1.7152, 'grad_norm': 0.8696802258491516, 'learning_rate': 6.722237916359825e-06, 'epoch': 0.4712, 'num_input_tokens_seen': 2470445041, 'completed': '47.12% (589 / 1_250)', 'remaining time': '6:23:08', 'throughput': '121337.94', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:29:27,928 >> {'loss': 1.7078, 'grad_norm': 0.26688095927238464, 'learning_rate': 6.710139192768695e-06, 'epoch': 0.472, 'num_input_tokens_seen': 2474639345, 'completed': '47.20% (590 / 1_250)', 'remaining time': '6:22:34', 'throughput': '118264.30', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:30:03,349 >> {'loss': 1.6466, 'grad_norm': 0.7066715359687805, 'learning_rate': 6.6980310322690515e-06, 'epoch': 0.4728, 'num_input_tokens_seen': 2478833649, 'completed': '47.28% (591 / 1_250)', 'remaining time': '6:22:00', 'throughput': '118413.04', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:30:38,634 >> {'loss': 1.5754, 'grad_norm': 0.43492937088012695, 'learning_rate': 6.685913529282758e-06, 'epoch': 0.4736, 'num_input_tokens_seen': 2483027953, 'completed': '47.36% (592 / 1_250)', 'remaining time': '6:21:26', 'throughput': '118869.28', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:31:09,990 >> {'loss': 1.6082, 'grad_norm': 0.29414036870002747, 'learning_rate': 6.673786778304538e-06, 'epoch': 0.4744, 'num_input_tokens_seen': 2487222257, 'completed': '47.44% (593 / 1_250)', 'remaining time': '6:20:47', 'throughput': '133764.45', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:31:41,935 >> {'loss': 1.6279, 'grad_norm': 0.6755964159965515, 'learning_rate': 6.66165087390123e-06, 'epoch': 0.4752, 'num_input_tokens_seen': 2491416561, 'completed': '47.52% (594 / 1_250)', 'remaining time': '6:20:09', 'throughput': '131299.15', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:32:13,937 >> {'loss': 1.6709, 'grad_norm': 0.32894542813301086, 'learning_rate': 6.649505910711058e-06, 'epoch': 0.476, 'num_input_tokens_seen': 2495610865, 'completed': '47.60% (595 / 1_250)', 'remaining time': '6:19:32', 'throughput': '131061.38', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:32:49,192 >> {'loss': 1.5558, 'grad_norm': 0.4994194209575653, 'learning_rate': 6.637351983442882e-06, 'epoch': 0.4768, 'num_input_tokens_seen': 2499805169, 'completed': '47.68% (596 / 1_250)', 'remaining time': '6:18:57', 'throughput': '118971.99', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:33:24,587 >> {'loss': 1.5322, 'grad_norm': 0.28472933173179626, 'learning_rate': 6.6251891868754704e-06, 'epoch': 0.4776, 'num_input_tokens_seen': 2503999473, 'completed': '47.76% (597 / 1_250)', 'remaining time': '6:18:23', 'throughput': '118498.24', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:33:59,673 >> {'loss': 1.6279, 'grad_norm': 0.25253885984420776, 'learning_rate': 6.613017615856752e-06, 'epoch': 0.4784, 'num_input_tokens_seen': 2508193777, 'completed': '47.84% (598 / 1_250)', 'remaining time': '6:17:49', 'throughput': '119543.78', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:34:35,137 >> {'loss': 1.619, 'grad_norm': 0.3701464831829071, 'learning_rate': 6.600837365303083e-06, 'epoch': 0.4792, 'num_input_tokens_seen': 2512388081, 'completed': '47.92% (599 / 1_250)', 'remaining time': '6:17:15', 'throughput': '118270.59', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:35:10,285 >> {'loss': 1.6601, 'grad_norm': 0.277951180934906, 'learning_rate': 6.588648530198505e-06, 'epoch': 0.48, 'num_input_tokens_seen': 2516582385, 'completed': '48.00% (600 / 1_250)', 'remaining time': '6:16:41', 'throughput': '119330.92', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:35:41,006 >> {'loss': 1.625, 'grad_norm': 0.3173031806945801, 'learning_rate': 6.5764512055940034e-06, 'epoch': 0.4808, 'num_input_tokens_seen': 2520776689, 'completed': '48.08% (601 / 1_250)', 'remaining time': '6:16:01', 'throughput': '136532.12', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:36:15,030 >> {'loss': 1.7335, 'grad_norm': 0.2676737308502197, 'learning_rate': 6.564245486606762e-06, 'epoch': 0.4816, 'num_input_tokens_seen': 2524970993, 'completed': '48.16% (602 / 1_250)', 'remaining time': '6:15:26', 'throughput': '123274.37', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:36:50,301 >> {'loss': 1.7545, 'grad_norm': 0.6356432437896729, 'learning_rate': 6.5520314684194316e-06, 'epoch': 0.4824, 'num_input_tokens_seen': 2529165297, 'completed': '48.24% (603 / 1_250)', 'remaining time': '6:14:52', 'throughput': '118914.74', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:37:25,715 >> {'loss': 1.8503, 'grad_norm': 0.35562437772750854, 'learning_rate': 6.5398092462793815e-06, 'epoch': 0.4832, 'num_input_tokens_seen': 2533359601, 'completed': '48.32% (604 / 1_250)', 'remaining time': '6:14:18', 'throughput': '118436.19', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:37:57,552 >> {'loss': 1.6925, 'grad_norm': 0.2692631781101227, 'learning_rate': 6.527578915497952e-06, 'epoch': 0.484, 'num_input_tokens_seen': 2537553905, 'completed': '48.40% (605 / 1_250)', 'remaining time': '6:13:40', 'throughput': '131744.29', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:38:32,813 >> {'loss': 1.6685, 'grad_norm': 0.28603553771972656, 'learning_rate': 6.515340571449719e-06, 'epoch': 0.4848, 'num_input_tokens_seen': 2541748209, 'completed': '48.48% (606 / 1_250)', 'remaining time': '6:13:05', 'throughput': '118950.13', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:39:07,898 >> {'loss': 1.7069, 'grad_norm': 0.4134010076522827, 'learning_rate': 6.503094309571752e-06, 'epoch': 0.4856, 'num_input_tokens_seen': 2545942513, 'completed': '48.56% (607 / 1_250)', 'remaining time': '6:12:31', 'throughput': '119546.85', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:39:39,257 >> {'loss': 1.655, 'grad_norm': 0.24852409958839417, 'learning_rate': 6.490840225362857e-06, 'epoch': 0.4864, 'num_input_tokens_seen': 2550136817, 'completed': '48.64% (608 / 1_250)', 'remaining time': '6:11:53', 'throughput': '133749.87', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:40:14,554 >> {'loss': 1.611, 'grad_norm': 0.3902679681777954, 'learning_rate': 6.478578414382847e-06, 'epoch': 0.4872, 'num_input_tokens_seen': 2554331121, 'completed': '48.72% (609 / 1_250)', 'remaining time': '6:11:18', 'throughput': '118830.47', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:40:45,773 >> {'loss': 1.706, 'grad_norm': 0.327660471200943, 'learning_rate': 6.466308972251786e-06, 'epoch': 0.488, 'num_input_tokens_seen': 2558525425, 'completed': '48.80% (610 / 1_250)', 'remaining time': '6:10:40', 'throughput': '134351.79', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:41:21,308 >> {'loss': 1.5951, 'grad_norm': 0.258598268032074, 'learning_rate': 6.454031994649247e-06, 'epoch': 0.4888, 'num_input_tokens_seen': 2562719729, 'completed': '48.88% (611 / 1_250)', 'remaining time': '6:10:06', 'throughput': '118033.02', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:41:56,541 >> {'loss': 1.535, 'grad_norm': 0.5117494463920593, 'learning_rate': 6.441747577313569e-06, 'epoch': 0.4896, 'num_input_tokens_seen': 2566914033, 'completed': '48.96% (612 / 1_250)', 'remaining time': '6:09:32', 'throughput': '119043.28', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:42:29,110 >> {'loss': 1.6392, 'grad_norm': 0.22583673894405365, 'learning_rate': 6.4294558160411055e-06, 'epoch': 0.4904, 'num_input_tokens_seen': 2571108337, 'completed': '49.04% (613 / 1_250)', 'remaining time': '6:08:55', 'throughput': '128781.28', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:43:04,376 >> {'loss': 1.5777, 'grad_norm': 0.29330018162727356, 'learning_rate': 6.417156806685483e-06, 'epoch': 0.4912, 'num_input_tokens_seen': 2575302641, 'completed': '49.12% (614 / 1_250)', 'remaining time': '6:08:21', 'throughput': '118935.89', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:43:39,802 >> {'loss': 1.491, 'grad_norm': 0.18678058683872223, 'learning_rate': 6.4048506451568416e-06, 'epoch': 0.492, 'num_input_tokens_seen': 2579496945, 'completed': '49.20% (615 / 1_250)', 'remaining time': '6:07:47', 'throughput': '118394.50', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:44:15,090 >> {'loss': 1.7357, 'grad_norm': 0.422293484210968, 'learning_rate': 6.392537427421105e-06, 'epoch': 0.4928, 'num_input_tokens_seen': 2583691249, 'completed': '49.28% (616 / 1_250)', 'remaining time': '6:07:12', 'throughput': '118859.20', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:44:50,446 >> {'loss': 1.5871, 'grad_norm': 0.40153244137763977, 'learning_rate': 6.380217249499217e-06, 'epoch': 0.4936, 'num_input_tokens_seen': 2587885553, 'completed': '49.36% (617 / 1_250)', 'remaining time': '6:06:38', 'throughput': '118631.02', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:45:24,713 >> {'loss': 1.4589, 'grad_norm': 0.198126420378685, 'learning_rate': 6.3678902074664e-06, 'epoch': 0.4944, 'num_input_tokens_seen': 2592079857, 'completed': '49.44% (618 / 1_250)', 'remaining time': '6:06:03', 'throughput': '122401.77', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:46:00,034 >> {'loss': 1.681, 'grad_norm': 0.45201823115348816, 'learning_rate': 6.355556397451407e-06, 'epoch': 0.4952, 'num_input_tokens_seen': 2596274161, 'completed': '49.52% (619 / 1_250)', 'remaining time': '6:05:29', 'throughput': '118748.06', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:46:34,202 >> {'loss': 1.8164, 'grad_norm': 0.4239669740200043, 'learning_rate': 6.343215915635762e-06, 'epoch': 0.496, 'num_input_tokens_seen': 2600468465, 'completed': '49.60% (620 / 1_250)', 'remaining time': '6:04:53', 'throughput': '122755.29', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:47:09,813 >> {'loss': 1.4629, 'grad_norm': 0.3408045768737793, 'learning_rate': 6.330868858253022e-06, 'epoch': 0.4968, 'num_input_tokens_seen': 2604662769, 'completed': '49.68% (621 / 1_250)', 'remaining time': '6:04:20', 'throughput': '117781.18', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:47:41,656 >> {'loss': 1.5866, 'grad_norm': 0.2929503321647644, 'learning_rate': 6.318515321588021e-06, 'epoch': 0.4976, 'num_input_tokens_seen': 2608857073, 'completed': '49.76% (622 / 1_250)', 'remaining time': '6:03:42', 'throughput': '131715.16', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:48:16,980 >> {'loss': 1.5577, 'grad_norm': 0.36821407079696655, 'learning_rate': 6.306155401976122e-06, 'epoch': 0.4984, 'num_input_tokens_seen': 2613051377, 'completed': '49.84% (623 / 1_250)', 'remaining time': '6:03:08', 'throughput': '118738.60', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:48:52,220 >> {'loss': 1.7855, 'grad_norm': 0.2494727075099945, 'learning_rate': 6.293789195802457e-06, 'epoch': 0.4992, 'num_input_tokens_seen': 2617245681, 'completed': '49.92% (624 / 1_250)', 'remaining time': '6:02:33', 'throughput': '119021.59', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:49:27,471 >> {'loss': 1.7065, 'grad_norm': 0.49916398525238037, 'learning_rate': 6.281416799501188e-06, 'epoch': 0.5, 'num_input_tokens_seen': 2621439985, 'completed': '50.00% (625 / 1_250)', 'remaining time': '6:01:59', 'throughput': '118985.76', 'gpu_mem_free': '16314MB'} +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:689: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +[INFO|trainer.py:3503] 2026-05-02 07:49:35,434 >> Saving model checkpoint to /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-625 +[INFO|configuration_utils.py:472] 2026-05-02 07:49:35,436 >> Configuration saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-625/config.json +[INFO|configuration_utils.py:807] 2026-05-02 07:49:35,436 >> Configuration saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-625/generation_config.json +[INFO|modeling_utils.py:2807] 2026-05-02 07:49:47,184 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 3 checkpoint shards. You can find where each parameters has been saved in the index located at /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-625/model.safetensors.index.json. +[INFO|tokenization_utils_base.py:2684] 2026-05-02 07:49:47,186 >> tokenizer config file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-625/tokenizer_config.json +[INFO|tokenization_utils_base.py:2693] 2026-05-02 07:49:47,186 >> Special tokens file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-625/special_tokens_map.json +[INFO|tokenization_utils_base.py:2684] 2026-05-02 07:49:55,680 >> tokenizer config file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/tokenizer_config.json +[INFO|tokenization_utils_base.py:2693] 2026-05-02 07:49:55,681 >> Special tokens file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/special_tokens_map.json +[INFO|trainer.py:3595] 2026-05-02 07:49:55,686 >> Deleting older checkpoint [/tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-500] due to args.save_total_limit +[WARNING|trainer.py:870] 2026-05-02 07:49:56,805 >> Save streaming dataset state: {'epoch': 0, 'sample_in_epoch': 160000, 'num_canonical_nodes': 2, 'shuffle_seed': 42, 'initial_physical_nodes': 2} +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/utils/checkpoint.py:1399: FutureWarning: `torch.cpu.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cpu', args...)` instead. + with device_autocast_ctx, torch.cpu.amp.autocast(**cpu_autocast_kwargs), recompute_context: # type: ignore[attr-defined] +[INFO|trainer.py:175] 2026-05-02 07:50:31,972 >> {'loss': 1.4131, 'grad_norm': 0.23181402683258057, 'learning_rate': 6.269038309554746e-06, 'epoch': 0.5008, 'num_input_tokens_seen': 2625634289, 'completed': '50.08% (626 / 1_250)', 'remaining time': '6:01:54', 'throughput': '65026.71', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:51:07,657 >> {'loss': 1.7518, 'grad_norm': 0.5845191478729248, 'learning_rate': 6.256653822493083e-06, 'epoch': 0.5016, 'num_input_tokens_seen': 2629828593, 'completed': '50.16% (627 / 1_250)', 'remaining time': '6:01:20', 'throughput': '117536.23', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:51:42,829 >> {'loss': 1.5142, 'grad_norm': 0.27147960662841797, 'learning_rate': 6.244263434892916e-06, 'epoch': 0.5024, 'num_input_tokens_seen': 2634022897, 'completed': '50.24% (628 / 1_250)', 'remaining time': '6:00:46', 'throughput': '119251.40', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:52:18,130 >> {'loss': 1.4807, 'grad_norm': 0.34898489713668823, 'learning_rate': 6.2318672433769765e-06, 'epoch': 0.5032, 'num_input_tokens_seen': 2638217201, 'completed': '50.32% (629 / 1_250)', 'remaining time': '6:00:11', 'throughput': '118814.72', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:52:53,390 >> {'loss': 1.3455, 'grad_norm': 0.23272676765918732, 'learning_rate': 6.219465344613258e-06, 'epoch': 0.504, 'num_input_tokens_seen': 2642411505, 'completed': '50.40% (630 / 1_250)', 'remaining time': '5:59:37', 'throughput': '118954.99', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:53:28,870 >> {'loss': 1.5129, 'grad_norm': 0.19673947989940643, 'learning_rate': 6.207057835314255e-06, 'epoch': 0.5048, 'num_input_tokens_seen': 2646605809, 'completed': '50.48% (631 / 1_250)', 'remaining time': '5:59:03', 'throughput': '118216.10', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:54:04,229 >> {'loss': 1.722, 'grad_norm': 0.5123729109764099, 'learning_rate': 6.194644812236222e-06, 'epoch': 0.5056, 'num_input_tokens_seen': 2650800113, 'completed': '50.56% (632 / 1_250)', 'remaining time': '5:58:29', 'throughput': '118619.37', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:54:35,367 >> {'loss': 1.6526, 'grad_norm': 0.35982179641723633, 'learning_rate': 6.1822263721784015e-06, 'epoch': 0.5064, 'num_input_tokens_seen': 2654994417, 'completed': '50.64% (633 / 1_250)', 'remaining time': '5:57:50', 'throughput': '134699.38', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:55:09,479 >> {'loss': 1.777, 'grad_norm': 0.3089689612388611, 'learning_rate': 6.1698026119822855e-06, 'epoch': 0.5072, 'num_input_tokens_seen': 2659188721, 'completed': '50.72% (634 / 1_250)', 'remaining time': '5:57:15', 'throughput': '122959.01', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:55:44,794 >> {'loss': 1.7003, 'grad_norm': 0.23806557059288025, 'learning_rate': 6.157373628530853e-06, 'epoch': 0.508, 'num_input_tokens_seen': 2663383025, 'completed': '50.80% (635 / 1_250)', 'remaining time': '5:56:41', 'throughput': '118767.11', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:56:20,041 >> {'loss': 1.6742, 'grad_norm': 0.4063676595687866, 'learning_rate': 6.144939518747813e-06, 'epoch': 0.5088, 'num_input_tokens_seen': 2667577329, 'completed': '50.88% (636 / 1_250)', 'remaining time': '5:56:06', 'throughput': '118996.70', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:56:55,219 >> {'loss': 1.7297, 'grad_norm': 0.39715996384620667, 'learning_rate': 6.13250037959685e-06, 'epoch': 0.5096, 'num_input_tokens_seen': 2671771632, 'completed': '50.96% (637 / 1_250)', 'remaining time': '5:55:32', 'throughput': '119231.00', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:57:30,465 >> {'loss': 1.6155, 'grad_norm': 0.25967246294021606, 'learning_rate': 6.120056308080872e-06, 'epoch': 0.5104, 'num_input_tokens_seen': 2675965936, 'completed': '51.04% (638 / 1_250)', 'remaining time': '5:54:57', 'throughput': '119001.47', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:58:04,665 >> {'loss': 1.6911, 'grad_norm': 0.2692367136478424, 'learning_rate': 6.107607401241247e-06, 'epoch': 0.5112, 'num_input_tokens_seen': 2680160240, 'completed': '51.12% (639 / 1_250)', 'remaining time': '5:54:22', 'throughput': '122640.07', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:58:39,820 >> {'loss': 1.4694, 'grad_norm': 0.3637540936470032, 'learning_rate': 6.095153756157052e-06, 'epoch': 0.512, 'num_input_tokens_seen': 2684354544, 'completed': '51.20% (640 / 1_250)', 'remaining time': '5:53:48', 'throughput': '119311.16', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:59:15,191 >> {'loss': 1.7008, 'grad_norm': 0.2901903986930847, 'learning_rate': 6.082695469944311e-06, 'epoch': 0.5128, 'num_input_tokens_seen': 2688548848, 'completed': '51.28% (641 / 1_250)', 'remaining time': '5:53:13', 'throughput': '118580.87', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 07:59:47,682 >> {'loss': 1.5568, 'grad_norm': 0.3350648581981659, 'learning_rate': 6.070232639755247e-06, 'epoch': 0.5136, 'num_input_tokens_seen': 2692743152, 'completed': '51.36% (642 / 1_250)', 'remaining time': '5:52:36', 'throughput': '129090.98', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:00:23,149 >> {'loss': 1.5189, 'grad_norm': 0.2424781620502472, 'learning_rate': 6.057765362777508e-06, 'epoch': 0.5144, 'num_input_tokens_seen': 2696937456, 'completed': '51.44% (643 / 1_250)', 'remaining time': '5:52:02', 'throughput': '118258.60', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:00:58,621 >> {'loss': 1.4646, 'grad_norm': 0.3288944661617279, 'learning_rate': 6.045293736233428e-06, 'epoch': 0.5152, 'num_input_tokens_seen': 2701131760, 'completed': '51.52% (644 / 1_250)', 'remaining time': '5:51:28', 'throughput': '118242.15', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:01:34,194 >> {'loss': 1.7315, 'grad_norm': 0.28515633940696716, 'learning_rate': 6.032817857379256e-06, 'epoch': 0.516, 'num_input_tokens_seen': 2705326064, 'completed': '51.60% (645 / 1_250)', 'remaining time': '5:50:54', 'throughput': '117905.85', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:02:09,410 >> {'loss': 1.5683, 'grad_norm': 0.26099804043769836, 'learning_rate': 6.020337823504398e-06, 'epoch': 0.5168, 'num_input_tokens_seen': 2709520368, 'completed': '51.68% (646 / 1_250)', 'remaining time': '5:50:19', 'throughput': '119102.65', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:02:40,779 >> {'loss': 1.7911, 'grad_norm': 0.43601444363594055, 'learning_rate': 6.007853731930667e-06, 'epoch': 0.5176, 'num_input_tokens_seen': 2713714672, 'completed': '51.76% (647 / 1_250)', 'remaining time': '5:49:41', 'throughput': '133710.58', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:03:15,288 >> {'loss': 1.7316, 'grad_norm': 0.4187580645084381, 'learning_rate': 5.99536568001152e-06, 'epoch': 0.5184, 'num_input_tokens_seen': 2717908976, 'completed': '51.84% (648 / 1_250)', 'remaining time': '5:49:06', 'throughput': '121540.86', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:03:49,922 >> {'loss': 1.6249, 'grad_norm': 0.316873699426651, 'learning_rate': 5.9828737651312905e-06, 'epoch': 0.5192, 'num_input_tokens_seen': 2722103280, 'completed': '51.92% (649 / 1_250)', 'remaining time': '5:48:31', 'throughput': '121104.76', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:04:21,443 >> {'loss': 1.6443, 'grad_norm': 0.3947019577026367, 'learning_rate': 5.970378084704441e-06, 'epoch': 0.52, 'num_input_tokens_seen': 2726297584, 'completed': '52.00% (650 / 1_250)', 'remaining time': '5:47:54', 'throughput': '133064.82', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:04:56,642 >> {'loss': 1.6403, 'grad_norm': 0.3091380298137665, 'learning_rate': 5.957878736174799e-06, 'epoch': 0.5208, 'num_input_tokens_seen': 2730491888, 'completed': '52.08% (651 / 1_250)', 'remaining time': '5:47:19', 'throughput': '119159.81', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:05:27,983 >> {'loss': 1.7486, 'grad_norm': 0.3958536386489868, 'learning_rate': 5.945375817014793e-06, 'epoch': 0.5216, 'num_input_tokens_seen': 2734686192, 'completed': '52.16% (652 / 1_250)', 'remaining time': '5:46:41', 'throughput': '133826.62', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:06:00,226 >> {'loss': 1.3961, 'grad_norm': 0.23812174797058105, 'learning_rate': 5.9328694247247e-06, 'epoch': 0.5224, 'num_input_tokens_seen': 2738880496, 'completed': '52.24% (653 / 1_250)', 'remaining time': '5:46:04', 'throughput': '130082.60', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:06:35,699 >> {'loss': 1.5831, 'grad_norm': 0.218031644821167, 'learning_rate': 5.920359656831879e-06, 'epoch': 0.5232, 'num_input_tokens_seen': 2743074800, 'completed': '52.32% (654 / 1_250)', 'remaining time': '5:45:30', 'throughput': '118240.41', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:07:11,189 >> {'loss': 1.4784, 'grad_norm': 0.43906617164611816, 'learning_rate': 5.907846610890012e-06, 'epoch': 0.524, 'num_input_tokens_seen': 2747269104, 'completed': '52.40% (655 / 1_250)', 'remaining time': '5:44:56', 'throughput': '118183.23', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:07:46,783 >> {'loss': 1.6463, 'grad_norm': 0.24094748497009277, 'learning_rate': 5.895330384478346e-06, 'epoch': 0.5248, 'num_input_tokens_seen': 2751463408, 'completed': '52.48% (656 / 1_250)', 'remaining time': '5:44:22', 'throughput': '117835.65', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:08:22,202 >> {'loss': 1.7127, 'grad_norm': 0.5821518898010254, 'learning_rate': 5.8828110752009275e-06, 'epoch': 0.5256, 'num_input_tokens_seen': 2755657712, 'completed': '52.56% (657 / 1_250)', 'remaining time': '5:43:48', 'throughput': '118422.14', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:08:56,911 >> {'loss': 1.5512, 'grad_norm': 0.27649766206741333, 'learning_rate': 5.870288780685846e-06, 'epoch': 0.5264, 'num_input_tokens_seen': 2759852016, 'completed': '52.64% (658 / 1_250)', 'remaining time': '5:43:13', 'throughput': '120841.41', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:09:32,156 >> {'loss': 1.6203, 'grad_norm': 0.6546261310577393, 'learning_rate': 5.857763598584469e-06, 'epoch': 0.5272, 'num_input_tokens_seen': 2764046320, 'completed': '52.72% (659 / 1_250)', 'remaining time': '5:42:38', 'throughput': '119003.71', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:10:07,406 >> {'loss': 1.7979, 'grad_norm': 0.31942930817604065, 'learning_rate': 5.845235626570684e-06, 'epoch': 0.528, 'num_input_tokens_seen': 2768240624, 'completed': '52.80% (660 / 1_250)', 'remaining time': '5:42:04', 'throughput': '118988.15', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:10:42,764 >> {'loss': 1.6893, 'grad_norm': 0.5326009392738342, 'learning_rate': 5.832704962340133e-06, 'epoch': 0.5288, 'num_input_tokens_seen': 2772434928, 'completed': '52.88% (661 / 1_250)', 'remaining time': '5:41:30', 'throughput': '118623.59', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:11:13,969 >> {'loss': 1.4753, 'grad_norm': 0.1866864562034607, 'learning_rate': 5.820171703609452e-06, 'epoch': 0.5296, 'num_input_tokens_seen': 2776629232, 'completed': '52.96% (662 / 1_250)', 'remaining time': '5:40:52', 'throughput': '134410.36', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:11:49,561 >> {'loss': 1.5367, 'grad_norm': 0.8463774919509888, 'learning_rate': 5.8076359481155095e-06, 'epoch': 0.5304, 'num_input_tokens_seen': 2780823536, 'completed': '53.04% (663 / 1_250)', 'remaining time': '5:40:18', 'throughput': '117843.33', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:12:22,390 >> {'loss': 1.6438, 'grad_norm': 0.4176541566848755, 'learning_rate': 5.795097793614648e-06, 'epoch': 0.5312, 'num_input_tokens_seen': 2785017840, 'completed': '53.12% (664 / 1_250)', 'remaining time': '5:39:41', 'throughput': '127764.29', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:12:56,797 >> {'loss': 1.5066, 'grad_norm': 0.4649841785430908, 'learning_rate': 5.782557337881911e-06, 'epoch': 0.532, 'num_input_tokens_seen': 2789212144, 'completed': '53.20% (665 / 1_250)', 'remaining time': '5:39:06', 'throughput': '121901.22', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:13:31,196 >> {'loss': 1.5951, 'grad_norm': 0.2137061357498169, 'learning_rate': 5.770014678710294e-06, 'epoch': 0.5328, 'num_input_tokens_seen': 2793406448, 'completed': '53.28% (666 / 1_250)', 'remaining time': '5:38:31', 'throughput': '121930.14', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:14:05,854 >> {'loss': 1.5867, 'grad_norm': 0.39038795232772827, 'learning_rate': 5.7574699139099725e-06, 'epoch': 0.5336, 'num_input_tokens_seen': 2797600752, 'completed': '53.36% (667 / 1_250)', 'remaining time': '5:37:56', 'throughput': '121020.36', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:14:41,198 >> {'loss': 1.7113, 'grad_norm': 0.4153537154197693, 'learning_rate': 5.744923141307541e-06, 'epoch': 0.5344, 'num_input_tokens_seen': 2801795056, 'completed': '53.44% (668 / 1_250)', 'remaining time': '5:37:22', 'throughput': '118669.58', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:15:16,510 >> {'loss': 1.6337, 'grad_norm': 0.3195401728153229, 'learning_rate': 5.732374458745256e-06, 'epoch': 0.5352, 'num_input_tokens_seen': 2805989360, 'completed': '53.52% (669 / 1_250)', 'remaining time': '5:36:47', 'throughput': '118779.25', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:15:51,802 >> {'loss': 1.6266, 'grad_norm': 0.5471029877662659, 'learning_rate': 5.719823964080261e-06, 'epoch': 0.536, 'num_input_tokens_seen': 2810183664, 'completed': '53.60% (670 / 1_250)', 'remaining time': '5:36:13', 'throughput': '118845.97', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:16:26,938 >> {'loss': 1.6638, 'grad_norm': 0.30566611886024475, 'learning_rate': 5.707271755183836e-06, 'epoch': 0.5368, 'num_input_tokens_seen': 2814377968, 'completed': '53.68% (671 / 1_250)', 'remaining time': '5:35:39', 'throughput': '119374.75', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:16:58,676 >> {'loss': 1.5665, 'grad_norm': 0.5117482542991638, 'learning_rate': 5.6947179299406276e-06, 'epoch': 0.5376, 'num_input_tokens_seen': 2818572272, 'completed': '53.76% (672 / 1_250)', 'remaining time': '5:35:01', 'throughput': '132152.06', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:17:33,816 >> {'loss': 1.6947, 'grad_norm': 0.2905639708042145, 'learning_rate': 5.682162586247887e-06, 'epoch': 0.5384, 'num_input_tokens_seen': 2822766576, 'completed': '53.84% (673 / 1_250)', 'remaining time': '5:34:27', 'throughput': '119359.35', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:18:09,094 >> {'loss': 1.7517, 'grad_norm': 0.5001528263092041, 'learning_rate': 5.669605822014706e-06, 'epoch': 0.5392, 'num_input_tokens_seen': 2826960880, 'completed': '53.92% (674 / 1_250)', 'remaining time': '5:33:52', 'throughput': '118894.02', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:18:43,401 >> {'loss': 1.7368, 'grad_norm': 0.32246172428131104, 'learning_rate': 5.657047735161256e-06, 'epoch': 0.54, 'num_input_tokens_seen': 2831155184, 'completed': '54.00% (675 / 1_250)', 'remaining time': '5:33:17', 'throughput': '122257.17', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:19:17,514 >> {'loss': 1.6243, 'grad_norm': 0.16792501509189606, 'learning_rate': 5.644488423618017e-06, 'epoch': 0.5408, 'num_input_tokens_seen': 2835349488, 'completed': '54.08% (676 / 1_250)', 'remaining time': '5:32:42', 'throughput': '122954.96', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:19:52,898 >> {'loss': 1.5275, 'grad_norm': 0.4812384843826294, 'learning_rate': 5.631927985325029e-06, 'epoch': 0.5416, 'num_input_tokens_seen': 2839543792, 'completed': '54.16% (677 / 1_250)', 'remaining time': '5:32:08', 'throughput': '118536.19', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:20:27,036 >> {'loss': 1.6338, 'grad_norm': 0.21749015152454376, 'learning_rate': 5.619366518231108e-06, 'epoch': 0.5424, 'num_input_tokens_seen': 2843738096, 'completed': '54.24% (678 / 1_250)', 'remaining time': '5:31:32', 'throughput': '122862.27', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:21:02,499 >> {'loss': 1.675, 'grad_norm': 0.4033973217010498, 'learning_rate': 5.6068041202931005e-06, 'epoch': 0.5432, 'num_input_tokens_seen': 2847932400, 'completed': '54.32% (679 / 1_250)', 'remaining time': '5:30:58', 'throughput': '118274.06', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:21:33,543 >> {'loss': 1.5014, 'grad_norm': 0.19860823452472687, 'learning_rate': 5.594240889475107e-06, 'epoch': 0.544, 'num_input_tokens_seen': 2852126704, 'completed': '54.40% (680 / 1_250)', 'remaining time': '5:30:20', 'throughput': '135109.15', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:22:07,961 >> {'loss': 1.7496, 'grad_norm': 0.39565855264663696, 'learning_rate': 5.581676923747727e-06, 'epoch': 0.5448, 'num_input_tokens_seen': 2856321008, 'completed': '54.48% (681 / 1_250)', 'remaining time': '5:29:45', 'throughput': '121863.67', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:22:43,363 >> {'loss': 1.6419, 'grad_norm': 0.4218910038471222, 'learning_rate': 5.569112321087289e-06, 'epoch': 0.5456, 'num_input_tokens_seen': 2860515312, 'completed': '54.56% (682 / 1_250)', 'remaining time': '5:29:11', 'throughput': '118474.10', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:23:18,556 >> {'loss': 1.7306, 'grad_norm': 0.17361138761043549, 'learning_rate': 5.556547179475088e-06, 'epoch': 0.5464, 'num_input_tokens_seen': 2864709616, 'completed': '54.64% (683 / 1_250)', 'remaining time': '5:28:36', 'throughput': '119182.52', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:23:53,995 >> {'loss': 1.6751, 'grad_norm': 0.43082958459854126, 'learning_rate': 5.543981596896621e-06, 'epoch': 0.5472, 'num_input_tokens_seen': 2868903919, 'completed': '54.72% (684 / 1_250)', 'remaining time': '5:28:02', 'throughput': '118352.11', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:24:29,355 >> {'loss': 1.6555, 'grad_norm': 0.4892142117023468, 'learning_rate': 5.531415671340827e-06, 'epoch': 0.548, 'num_input_tokens_seen': 2873098223, 'completed': '54.80% (685 / 1_250)', 'remaining time': '5:27:28', 'throughput': '118616.19', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:25:00,095 >> {'loss': 1.7752, 'grad_norm': 0.47719189524650574, 'learning_rate': 5.518849500799318e-06, 'epoch': 0.5488, 'num_input_tokens_seen': 2877292527, 'completed': '54.88% (686 / 1_250)', 'remaining time': '5:26:50', 'throughput': '136446.11', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:25:35,391 >> {'loss': 1.4658, 'grad_norm': 0.34813982248306274, 'learning_rate': 5.506283183265616e-06, 'epoch': 0.5496, 'num_input_tokens_seen': 2881486831, 'completed': '54.96% (687 / 1_250)', 'remaining time': '5:26:15', 'throughput': '118832.05', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:26:10,760 >> {'loss': 1.4384, 'grad_norm': 0.2537268102169037, 'learning_rate': 5.493716816734386e-06, 'epoch': 0.5504, 'num_input_tokens_seen': 2885681135, 'completed': '55.04% (688 / 1_250)', 'remaining time': '5:25:41', 'throughput': '118587.93', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:26:46,062 >> {'loss': 1.5409, 'grad_norm': 0.44643357396125793, 'learning_rate': 5.4811504992006835e-06, 'epoch': 0.5512, 'num_input_tokens_seen': 2889875439, 'completed': '55.12% (689 / 1_250)', 'remaining time': '5:25:07', 'throughput': '118808.97', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:27:16,887 >> {'loss': 1.4666, 'grad_norm': 0.3694015145301819, 'learning_rate': 5.468584328659173e-06, 'epoch': 0.552, 'num_input_tokens_seen': 2894069743, 'completed': '55.20% (690 / 1_250)', 'remaining time': '5:24:29', 'throughput': '136070.89', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:27:52,264 >> {'loss': 1.6761, 'grad_norm': 0.7657492160797119, 'learning_rate': 5.45601840310338e-06, 'epoch': 0.5528, 'num_input_tokens_seen': 2898264047, 'completed': '55.28% (691 / 1_250)', 'remaining time': '5:23:55', 'throughput': '118558.20', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:28:26,694 >> {'loss': 1.6281, 'grad_norm': 0.29115062952041626, 'learning_rate': 5.443452820524914e-06, 'epoch': 0.5536, 'num_input_tokens_seen': 2902458351, 'completed': '55.36% (692 / 1_250)', 'remaining time': '5:23:20', 'throughput': '121822.23', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:29:02,258 >> {'loss': 1.5654, 'grad_norm': 0.4553484320640564, 'learning_rate': 5.430887678912712e-06, 'epoch': 0.5544, 'num_input_tokens_seen': 2906652655, 'completed': '55.44% (693 / 1_250)', 'remaining time': '5:22:45', 'throughput': '117937.44', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:29:37,510 >> {'loss': 1.7923, 'grad_norm': 0.3951619863510132, 'learning_rate': 5.418323076252274e-06, 'epoch': 0.5552, 'num_input_tokens_seen': 2910846959, 'completed': '55.52% (694 / 1_250)', 'remaining time': '5:22:11', 'throughput': '118981.13', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:30:12,073 >> {'loss': 1.6881, 'grad_norm': 0.5095964670181274, 'learning_rate': 5.405759110524894e-06, 'epoch': 0.556, 'num_input_tokens_seen': 2915041263, 'completed': '55.60% (695 / 1_250)', 'remaining time': '5:21:36', 'throughput': '121350.68', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:30:47,316 >> {'loss': 1.6544, 'grad_norm': 0.3493673801422119, 'learning_rate': 5.393195879706903e-06, 'epoch': 0.5568, 'num_input_tokens_seen': 2919235567, 'completed': '55.68% (696 / 1_250)', 'remaining time': '5:21:02', 'throughput': '119013.20', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:31:22,299 >> {'loss': 1.6837, 'grad_norm': 0.3740013837814331, 'learning_rate': 5.380633481768893e-06, 'epoch': 0.5576, 'num_input_tokens_seen': 2923429871, 'completed': '55.76% (697 / 1_250)', 'remaining time': '5:20:27', 'throughput': '119892.54', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:31:57,586 >> {'loss': 1.568, 'grad_norm': 0.29592350125312805, 'learning_rate': 5.368072014674973e-06, 'epoch': 0.5584, 'num_input_tokens_seen': 2927624175, 'completed': '55.84% (698 / 1_250)', 'remaining time': '5:19:53', 'throughput': '118865.70', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:32:31,604 >> {'loss': 1.6563, 'grad_norm': 0.2861212193965912, 'learning_rate': 5.355511576381983e-06, 'epoch': 0.5592, 'num_input_tokens_seen': 2931818479, 'completed': '55.92% (699 / 1_250)', 'remaining time': '5:19:17', 'throughput': '123294.70', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:33:06,793 >> {'loss': 1.6685, 'grad_norm': 0.21806608140468597, 'learning_rate': 5.342952264838748e-06, 'epoch': 0.56, 'num_input_tokens_seen': 2936012783, 'completed': '56.00% (700 / 1_250)', 'remaining time': '5:18:43', 'throughput': '119192.64', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:33:37,541 >> {'loss': 1.5914, 'grad_norm': 0.2485124170780182, 'learning_rate': 5.330394177985295e-06, 'epoch': 0.5608, 'num_input_tokens_seen': 2940207087, 'completed': '56.08% (701 / 1_250)', 'remaining time': '5:18:05', 'throughput': '136410.89', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:34:12,719 >> {'loss': 1.5879, 'grad_norm': 0.1893700510263443, 'learning_rate': 5.317837413752115e-06, 'epoch': 0.5616, 'num_input_tokens_seen': 2944401391, 'completed': '56.16% (702 / 1_250)', 'remaining time': '5:17:31', 'throughput': '119229.20', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:34:44,510 >> {'loss': 1.593, 'grad_norm': 0.2361913025379181, 'learning_rate': 5.305282070059375e-06, 'epoch': 0.5624, 'num_input_tokens_seen': 2948595695, 'completed': '56.24% (703 / 1_250)', 'remaining time': '5:16:54', 'throughput': '131936.64', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:35:16,013 >> {'loss': 1.4407, 'grad_norm': 0.1815735548734665, 'learning_rate': 5.292728244816164e-06, 'epoch': 0.5632, 'num_input_tokens_seen': 2952789999, 'completed': '56.32% (704 / 1_250)', 'remaining time': '5:16:16', 'throughput': '133138.05', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:35:50,501 >> {'loss': 1.66, 'grad_norm': 0.21186697483062744, 'learning_rate': 5.280176035919741e-06, 'epoch': 0.564, 'num_input_tokens_seen': 2956984303, 'completed': '56.40% (705 / 1_250)', 'remaining time': '5:15:41', 'throughput': '121615.67', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:36:26,105 >> {'loss': 1.4157, 'grad_norm': 0.4290787875652313, 'learning_rate': 5.267625541254746e-06, 'epoch': 0.5648, 'num_input_tokens_seen': 2961178607, 'completed': '56.48% (706 / 1_250)', 'remaining time': '5:15:07', 'throughput': '117804.03', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:37:01,335 >> {'loss': 1.4891, 'grad_norm': 0.3181263506412506, 'learning_rate': 5.255076858692461e-06, 'epoch': 0.5656, 'num_input_tokens_seen': 2965372911, 'completed': '56.56% (707 / 1_250)', 'remaining time': '5:14:33', 'throughput': '119056.68', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:37:32,641 >> {'loss': 1.5408, 'grad_norm': 0.19151104986667633, 'learning_rate': 5.242530086090029e-06, 'epoch': 0.5664, 'num_input_tokens_seen': 2969567215, 'completed': '56.64% (708 / 1_250)', 'remaining time': '5:13:55', 'throughput': '133977.70', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:38:06,681 >> {'loss': 1.7267, 'grad_norm': 0.30933627486228943, 'learning_rate': 5.229985321289709e-06, 'epoch': 0.5672, 'num_input_tokens_seen': 2973761519, 'completed': '56.72% (709 / 1_250)', 'remaining time': '5:13:20', 'throughput': '123218.16', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:38:42,095 >> {'loss': 1.4746, 'grad_norm': 0.2851998507976532, 'learning_rate': 5.217442662118091e-06, 'epoch': 0.568, 'num_input_tokens_seen': 2977955823, 'completed': '56.80% (710 / 1_250)', 'remaining time': '5:12:46', 'throughput': '118433.45', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:39:17,417 >> {'loss': 1.7199, 'grad_norm': 0.23848627507686615, 'learning_rate': 5.204902206385355e-06, 'epoch': 0.5688, 'num_input_tokens_seen': 2982150127, 'completed': '56.88% (711 / 1_250)', 'remaining time': '5:12:12', 'throughput': '118746.36', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:39:52,784 >> {'loss': 1.5195, 'grad_norm': 0.2846120297908783, 'learning_rate': 5.192364051884492e-06, 'epoch': 0.5696, 'num_input_tokens_seen': 2986344431, 'completed': '56.96% (712 / 1_250)', 'remaining time': '5:11:37', 'throughput': '118591.76', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:40:27,829 >> {'loss': 1.5221, 'grad_norm': 0.21977123618125916, 'learning_rate': 5.179828296390551e-06, 'epoch': 0.5704, 'num_input_tokens_seen': 2990538735, 'completed': '57.04% (713 / 1_250)', 'remaining time': '5:11:03', 'throughput': '119684.16', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:41:03,232 >> {'loss': 1.506, 'grad_norm': 0.25173938274383545, 'learning_rate': 5.1672950376598685e-06, 'epoch': 0.5712, 'num_input_tokens_seen': 2994733039, 'completed': '57.12% (714 / 1_250)', 'remaining time': '5:10:28', 'throughput': '118474.25', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:41:38,685 >> {'loss': 1.6613, 'grad_norm': 0.20726050436496735, 'learning_rate': 5.1547643734293165e-06, 'epoch': 0.572, 'num_input_tokens_seen': 2998927343, 'completed': '57.20% (715 / 1_250)', 'remaining time': '5:09:54', 'throughput': '118304.42', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:42:14,030 >> {'loss': 1.583, 'grad_norm': 0.5145110487937927, 'learning_rate': 5.142236401415532e-06, 'epoch': 0.5728, 'num_input_tokens_seen': 3003121647, 'completed': '57.28% (716 / 1_250)', 'remaining time': '5:09:20', 'throughput': '118668.70', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:42:49,202 >> {'loss': 1.5887, 'grad_norm': 0.4368215501308441, 'learning_rate': 5.1297112193141555e-06, 'epoch': 0.5736, 'num_input_tokens_seen': 3007315951, 'completed': '57.36% (717 / 1_250)', 'remaining time': '5:08:45', 'throughput': '119251.55', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:43:24,303 >> {'loss': 1.6471, 'grad_norm': 0.33399492502212524, 'learning_rate': 5.117188924799075e-06, 'epoch': 0.5744, 'num_input_tokens_seen': 3011510255, 'completed': '57.44% (718 / 1_250)', 'remaining time': '5:08:11', 'throughput': '119492.91', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:43:59,713 >> {'loss': 1.4643, 'grad_norm': 0.361404687166214, 'learning_rate': 5.104669615521657e-06, 'epoch': 0.5752, 'num_input_tokens_seen': 3015704559, 'completed': '57.52% (719 / 1_250)', 'remaining time': '5:07:37', 'throughput': '118450.57', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:44:35,173 >> {'loss': 1.7383, 'grad_norm': 0.4034412205219269, 'learning_rate': 5.092153389109991e-06, 'epoch': 0.576, 'num_input_tokens_seen': 3019898862, 'completed': '57.60% (720 / 1_250)', 'remaining time': '5:07:02', 'throughput': '118280.78', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:45:10,350 >> {'loss': 1.5904, 'grad_norm': 0.3955073654651642, 'learning_rate': 5.079640343168123e-06, 'epoch': 0.5768, 'num_input_tokens_seen': 3024093166, 'completed': '57.68% (721 / 1_250)', 'remaining time': '5:06:28', 'throughput': '119235.03', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:45:45,580 >> {'loss': 1.5712, 'grad_norm': 0.359293133020401, 'learning_rate': 5.067130575275303e-06, 'epoch': 0.5776, 'num_input_tokens_seen': 3028287470, 'completed': '57.76% (722 / 1_250)', 'remaining time': '5:05:54', 'throughput': '119053.78', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:46:21,047 >> {'loss': 1.6426, 'grad_norm': 0.20716886222362518, 'learning_rate': 5.054624182985208e-06, 'epoch': 0.5784, 'num_input_tokens_seen': 3032481774, 'completed': '57.84% (723 / 1_250)', 'remaining time': '5:05:19', 'throughput': '118259.35', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:46:56,391 >> {'loss': 1.6652, 'grad_norm': 0.40728217363357544, 'learning_rate': 5.0421212638252025e-06, 'epoch': 0.5792, 'num_input_tokens_seen': 3036676078, 'completed': '57.92% (724 / 1_250)', 'remaining time': '5:04:45', 'throughput': '118670.74', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:47:31,531 >> {'loss': 1.5872, 'grad_norm': 0.25652727484703064, 'learning_rate': 5.02962191529556e-06, 'epoch': 0.58, 'num_input_tokens_seen': 3040870382, 'completed': '58.00% (725 / 1_250)', 'remaining time': '5:04:10', 'throughput': '119359.72', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:48:06,543 >> {'loss': 1.6409, 'grad_norm': 0.32650890946388245, 'learning_rate': 5.01712623486871e-06, 'epoch': 0.5808, 'num_input_tokens_seen': 3045064686, 'completed': '58.08% (726 / 1_250)', 'remaining time': '5:03:36', 'throughput': '119797.12', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:48:41,771 >> {'loss': 1.784, 'grad_norm': 0.42432263493537903, 'learning_rate': 5.0046343199884815e-06, 'epoch': 0.5816, 'num_input_tokens_seen': 3049258990, 'completed': '58.16% (727 / 1_250)', 'remaining time': '5:03:01', 'throughput': '119061.24', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:49:17,307 >> {'loss': 1.5858, 'grad_norm': 0.5314838886260986, 'learning_rate': 4.992146268069334e-06, 'epoch': 0.5824, 'num_input_tokens_seen': 3053453294, 'completed': '58.24% (728 / 1_250)', 'remaining time': '5:02:27', 'throughput': '118031.03', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:49:52,496 >> {'loss': 1.6653, 'grad_norm': 0.7088274955749512, 'learning_rate': 4.979662176495604e-06, 'epoch': 0.5832, 'num_input_tokens_seen': 3057647598, 'completed': '58.32% (729 / 1_250)', 'remaining time': '5:01:53', 'throughput': '119192.30', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:50:23,278 >> {'loss': 1.5872, 'grad_norm': 0.35402777791023254, 'learning_rate': 4.967182142620746e-06, 'epoch': 0.584, 'num_input_tokens_seen': 3061841902, 'completed': '58.40% (730 / 1_250)', 'remaining time': '5:01:15', 'throughput': '136260.70', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:50:58,597 >> {'loss': 1.4144, 'grad_norm': 0.6921590566635132, 'learning_rate': 4.954706263766575e-06, 'epoch': 0.5848, 'num_input_tokens_seen': 3066036206, 'completed': '58.48% (731 / 1_250)', 'remaining time': '5:00:41', 'throughput': '118753.79', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:51:33,894 >> {'loss': 1.561, 'grad_norm': 0.31091880798339844, 'learning_rate': 4.942234637222493e-06, 'epoch': 0.5856, 'num_input_tokens_seen': 3070230510, 'completed': '58.56% (732 / 1_250)', 'remaining time': '5:00:06', 'throughput': '118830.31', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:52:09,301 >> {'loss': 1.4717, 'grad_norm': 0.44953274726867676, 'learning_rate': 4.929767360244756e-06, 'epoch': 0.5864, 'num_input_tokens_seen': 3074424814, 'completed': '58.64% (733 / 1_250)', 'remaining time': '4:59:32', 'throughput': '118457.86', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:52:44,547 >> {'loss': 1.5734, 'grad_norm': 0.5207445621490479, 'learning_rate': 4.9173045300556895e-06, 'epoch': 0.5872, 'num_input_tokens_seen': 3078619118, 'completed': '58.72% (734 / 1_250)', 'remaining time': '4:58:58', 'throughput': '119002.28', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:53:19,993 >> {'loss': 1.6888, 'grad_norm': 0.396379292011261, 'learning_rate': 4.904846243842949e-06, 'epoch': 0.588, 'num_input_tokens_seen': 3082813422, 'completed': '58.80% (735 / 1_250)', 'remaining time': '4:58:23', 'throughput': '118329.84', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:53:55,397 >> {'loss': 1.6189, 'grad_norm': 0.47968605160713196, 'learning_rate': 4.892392598758754e-06, 'epoch': 0.5888, 'num_input_tokens_seen': 3087007726, 'completed': '58.88% (736 / 1_250)', 'remaining time': '4:57:49', 'throughput': '118468.44', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:54:30,750 >> {'loss': 1.6298, 'grad_norm': 0.2811976671218872, 'learning_rate': 4.87994369191913e-06, 'epoch': 0.5896, 'num_input_tokens_seen': 3091202030, 'completed': '58.96% (737 / 1_250)', 'remaining time': '4:57:15', 'throughput': '118641.02', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:55:06,115 >> {'loss': 1.7023, 'grad_norm': 0.46520552039146423, 'learning_rate': 4.867499620403152e-06, 'epoch': 0.5904, 'num_input_tokens_seen': 3095396334, 'completed': '59.04% (738 / 1_250)', 'remaining time': '4:56:40', 'throughput': '118598.75', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:55:41,395 >> {'loss': 1.5602, 'grad_norm': 0.3069274127483368, 'learning_rate': 4.855060481252188e-06, 'epoch': 0.5912, 'num_input_tokens_seen': 3099590638, 'completed': '59.12% (739 / 1_250)', 'remaining time': '4:56:06', 'throughput': '118887.38', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:56:16,525 >> {'loss': 1.7271, 'grad_norm': 0.336331844329834, 'learning_rate': 4.842626371469149e-06, 'epoch': 0.592, 'num_input_tokens_seen': 3103784942, 'completed': '59.20% (740 / 1_250)', 'remaining time': '4:55:31', 'throughput': '119392.90', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:56:51,989 >> {'loss': 1.5721, 'grad_norm': 0.18960033357143402, 'learning_rate': 4.830197388017716e-06, 'epoch': 0.5928, 'num_input_tokens_seen': 3107979245, 'completed': '59.28% (741 / 1_250)', 'remaining time': '4:54:57', 'throughput': '118271.45', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:57:27,188 >> {'loss': 1.7154, 'grad_norm': 0.21673670411109924, 'learning_rate': 4.817773627821602e-06, 'epoch': 0.5936, 'num_input_tokens_seen': 3112173549, 'completed': '59.36% (742 / 1_250)', 'remaining time': '4:54:23', 'throughput': '119159.57', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:58:02,406 >> {'loss': 1.8341, 'grad_norm': 0.27001339197158813, 'learning_rate': 4.8053551877637806e-06, 'epoch': 0.5944, 'num_input_tokens_seen': 3116367853, 'completed': '59.44% (743 / 1_250)', 'remaining time': '4:53:48', 'throughput': '119093.35', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:58:37,629 >> {'loss': 1.6089, 'grad_norm': 0.20217734575271606, 'learning_rate': 4.792942164685748e-06, 'epoch': 0.5952, 'num_input_tokens_seen': 3120562157, 'completed': '59.52% (744 / 1_250)', 'remaining time': '4:53:14', 'throughput': '119080.43', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:59:12,956 >> {'loss': 1.8232, 'grad_norm': 0.45962366461753845, 'learning_rate': 4.780534655386744e-06, 'epoch': 0.596, 'num_input_tokens_seen': 3124756461, 'completed': '59.60% (745 / 1_250)', 'remaining time': '4:52:39', 'throughput': '118726.99', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 08:59:48,240 >> {'loss': 1.7157, 'grad_norm': 0.40630361437797546, 'learning_rate': 4.768132756623024e-06, 'epoch': 0.5968, 'num_input_tokens_seen': 3128950765, 'completed': '59.68% (746 / 1_250)', 'remaining time': '4:52:05', 'throughput': '118872.82', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:00:23,525 >> {'loss': 1.7768, 'grad_norm': 0.3115631341934204, 'learning_rate': 4.755736565107087e-06, 'epoch': 0.5976, 'num_input_tokens_seen': 3133145069, 'completed': '59.76% (747 / 1_250)', 'remaining time': '4:51:31', 'throughput': '118869.43', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:00:58,988 >> {'loss': 1.5551, 'grad_norm': 0.27269601821899414, 'learning_rate': 4.743346177506919e-06, 'epoch': 0.5984, 'num_input_tokens_seen': 3137339373, 'completed': '59.84% (748 / 1_250)', 'remaining time': '4:50:56', 'throughput': '118271.63', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:01:34,236 >> {'loss': 1.499, 'grad_norm': 0.276258260011673, 'learning_rate': 4.730961690445256e-06, 'epoch': 0.5992, 'num_input_tokens_seen': 3141533677, 'completed': '59.92% (749 / 1_250)', 'remaining time': '4:50:22', 'throughput': '118995.39', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:02:09,762 >> {'loss': 1.4312, 'grad_norm': 0.33442020416259766, 'learning_rate': 4.718583200498814e-06, 'epoch': 0.6, 'num_input_tokens_seen': 3145727981, 'completed': '60.00% (750 / 1_250)', 'remaining time': '4:49:47', 'throughput': '118062.12', 'gpu_mem_free': '16314MB'} +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:689: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +[INFO|trainer.py:3503] 2026-05-02 09:02:18,881 >> Saving model checkpoint to /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-750 +[INFO|configuration_utils.py:472] 2026-05-02 09:02:18,883 >> Configuration saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-750/config.json +[INFO|configuration_utils.py:807] 2026-05-02 09:02:18,883 >> Configuration saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-750/generation_config.json +[INFO|modeling_utils.py:2807] 2026-05-02 09:02:32,070 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 3 checkpoint shards. You can find where each parameters has been saved in the index located at /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-750/model.safetensors.index.json. +[INFO|tokenization_utils_base.py:2684] 2026-05-02 09:02:32,072 >> tokenizer config file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-750/tokenizer_config.json +[INFO|tokenization_utils_base.py:2693] 2026-05-02 09:02:32,072 >> Special tokens file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-750/special_tokens_map.json +[INFO|tokenization_utils_base.py:2684] 2026-05-02 09:02:42,428 >> tokenizer config file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/tokenizer_config.json +[INFO|tokenization_utils_base.py:2693] 2026-05-02 09:02:42,429 >> Special tokens file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/special_tokens_map.json +[INFO|trainer.py:3595] 2026-05-02 09:02:42,444 >> Deleting older checkpoint [/tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-625] due to args.save_total_limit +[WARNING|trainer.py:870] 2026-05-02 09:02:43,668 >> Save streaming dataset state: {'epoch': 0, 'sample_in_epoch': 192000, 'num_canonical_nodes': 2, 'shuffle_seed': 42, 'initial_physical_nodes': 2} +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/utils/checkpoint.py:1399: FutureWarning: `torch.cpu.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cpu', args...)` instead. + with device_autocast_ctx, torch.cpu.amp.autocast(**cpu_autocast_kwargs), recompute_context: # type: ignore[attr-defined] +[INFO|trainer.py:175] 2026-05-02 09:03:19,026 >> {'loss': 1.6294, 'grad_norm': 0.25142383575439453, 'learning_rate': 4.706210804197545e-06, 'epoch': 0.6008, 'num_input_tokens_seen': 3149922285, 'completed': '60.08% (751 / 1_250)', 'remaining time': '4:49:36', 'throughput': '60555.05', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:03:50,365 >> {'loss': 1.4455, 'grad_norm': 0.3335058093070984, 'learning_rate': 4.6938445980238805e-06, 'epoch': 0.6016, 'num_input_tokens_seen': 3154116589, 'completed': '60.16% (752 / 1_250)', 'remaining time': '4:48:58', 'throughput': '133838.26', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:04:25,587 >> {'loss': 1.6023, 'grad_norm': 0.24268297851085663, 'learning_rate': 4.68148467841198e-06, 'epoch': 0.6024, 'num_input_tokens_seen': 3158310893, 'completed': '60.24% (753 / 1_250)', 'remaining time': '4:48:24', 'throughput': '119081.07', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:05:00,700 >> {'loss': 1.4157, 'grad_norm': 0.25243985652923584, 'learning_rate': 4.66913114174698e-06, 'epoch': 0.6032, 'num_input_tokens_seen': 3162505197, 'completed': '60.32% (754 / 1_250)', 'remaining time': '4:47:49', 'throughput': '119451.73', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:05:36,214 >> {'loss': 1.6791, 'grad_norm': 0.35761696100234985, 'learning_rate': 4.656784084364239e-06, 'epoch': 0.604, 'num_input_tokens_seen': 3166699501, 'completed': '60.40% (755 / 1_250)', 'remaining time': '4:47:15', 'throughput': '118102.26', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:06:11,538 >> {'loss': 1.6612, 'grad_norm': 0.19959819316864014, 'learning_rate': 4.644443602548595e-06, 'epoch': 0.6048, 'num_input_tokens_seen': 3170893805, 'completed': '60.48% (756 / 1_250)', 'remaining time': '4:46:40', 'throughput': '118739.68', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:06:45,809 >> {'loss': 1.6859, 'grad_norm': 0.49494120478630066, 'learning_rate': 4.632109792533599e-06, 'epoch': 0.6056, 'num_input_tokens_seen': 3175088109, 'completed': '60.56% (757 / 1_250)', 'remaining time': '4:46:05', 'throughput': '122387.91', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:07:21,006 >> {'loss': 1.6222, 'grad_norm': 0.2546500563621521, 'learning_rate': 4.619782750500784e-06, 'epoch': 0.6064, 'num_input_tokens_seen': 3179282413, 'completed': '60.64% (758 / 1_250)', 'remaining time': '4:45:31', 'throughput': '119164.05', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:07:55,464 >> {'loss': 1.4814, 'grad_norm': 0.3268519937992096, 'learning_rate': 4.607462572578897e-06, 'epoch': 0.6072, 'num_input_tokens_seen': 3183476717, 'completed': '60.72% (759 / 1_250)', 'remaining time': '4:44:56', 'throughput': '121723.33', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:08:30,622 >> {'loss': 1.503, 'grad_norm': 0.48450732231140137, 'learning_rate': 4.595149354843161e-06, 'epoch': 0.608, 'num_input_tokens_seen': 3187671021, 'completed': '60.80% (760 / 1_250)', 'remaining time': '4:44:21', 'throughput': '119297.48', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:09:06,006 >> {'loss': 1.5922, 'grad_norm': 0.1736665666103363, 'learning_rate': 4.582843193314519e-06, 'epoch': 0.6088, 'num_input_tokens_seen': 3191865325, 'completed': '60.88% (761 / 1_250)', 'remaining time': '4:43:47', 'throughput': '118538.22', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:09:41,444 >> {'loss': 1.6297, 'grad_norm': 0.5184677243232727, 'learning_rate': 4.570544183958896e-06, 'epoch': 0.6096, 'num_input_tokens_seen': 3196059629, 'completed': '60.96% (762 / 1_250)', 'remaining time': '4:43:12', 'throughput': '118354.97', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:10:15,050 >> {'loss': 1.766, 'grad_norm': 0.38085299730300903, 'learning_rate': 4.558252422686433e-06, 'epoch': 0.6104, 'num_input_tokens_seen': 3200253933, 'completed': '61.04% (763 / 1_250)', 'remaining time': '4:42:37', 'throughput': '124809.19', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:10:50,422 >> {'loss': 1.7088, 'grad_norm': 0.5382132530212402, 'learning_rate': 4.545968005350756e-06, 'epoch': 0.6112, 'num_input_tokens_seen': 3204448237, 'completed': '61.12% (764 / 1_250)', 'remaining time': '4:42:02', 'throughput': '118577.71', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:11:24,393 >> {'loss': 1.7691, 'grad_norm': 0.48918095231056213, 'learning_rate': 4.533691027748216e-06, 'epoch': 0.612, 'num_input_tokens_seen': 3208642541, 'completed': '61.20% (765 / 1_250)', 'remaining time': '4:41:27', 'throughput': '123465.23', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:11:59,554 >> {'loss': 1.7944, 'grad_norm': 0.2659469544887543, 'learning_rate': 4.521421585617154e-06, 'epoch': 0.6128, 'num_input_tokens_seen': 3212836845, 'completed': '61.28% (766 / 1_250)', 'remaining time': '4:40:52', 'throughput': '119289.43', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:12:34,859 >> {'loss': 1.6066, 'grad_norm': 0.47804221510887146, 'learning_rate': 4.509159774637144e-06, 'epoch': 0.6136, 'num_input_tokens_seen': 3217031149, 'completed': '61.36% (767 / 1_250)', 'remaining time': '4:40:18', 'throughput': '118801.62', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:13:10,062 >> {'loss': 1.453, 'grad_norm': 0.18225257098674774, 'learning_rate': 4.496905690428248e-06, 'epoch': 0.6144, 'num_input_tokens_seen': 3221225453, 'completed': '61.44% (768 / 1_250)', 'remaining time': '4:39:43', 'throughput': '119147.45', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:13:41,348 >> {'loss': 1.5609, 'grad_norm': 0.2918648421764374, 'learning_rate': 4.484659428550282e-06, 'epoch': 0.6152, 'num_input_tokens_seen': 3225419757, 'completed': '61.52% (769 / 1_250)', 'remaining time': '4:39:06', 'throughput': '134061.34', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:14:15,353 >> {'loss': 1.5575, 'grad_norm': 0.3114336431026459, 'learning_rate': 4.4724210845020495e-06, 'epoch': 0.616, 'num_input_tokens_seen': 3229614061, 'completed': '61.60% (770 / 1_250)', 'remaining time': '4:38:31', 'throughput': '123343.84', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:14:50,627 >> {'loss': 1.4075, 'grad_norm': 0.1917589157819748, 'learning_rate': 4.460190753720622e-06, 'epoch': 0.6168, 'num_input_tokens_seen': 3233808365, 'completed': '61.68% (771 / 1_250)', 'remaining time': '4:37:56', 'throughput': '118907.94', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:15:21,514 >> {'loss': 1.6279, 'grad_norm': 0.5499981045722961, 'learning_rate': 4.44796853158057e-06, 'epoch': 0.6176, 'num_input_tokens_seen': 3238002669, 'completed': '61.76% (772 / 1_250)', 'remaining time': '4:37:19', 'throughput': '135792.36', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:15:56,369 >> {'loss': 1.3944, 'grad_norm': 0.27061301469802856, 'learning_rate': 4.43575451339324e-06, 'epoch': 0.6184, 'num_input_tokens_seen': 3242196973, 'completed': '61.84% (773 / 1_250)', 'remaining time': '4:36:44', 'throughput': '120338.30', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:16:31,523 >> {'loss': 1.7356, 'grad_norm': 0.3246423304080963, 'learning_rate': 4.423548794405999e-06, 'epoch': 0.6192, 'num_input_tokens_seen': 3246391277, 'completed': '61.92% (774 / 1_250)', 'remaining time': '4:36:10', 'throughput': '119312.51', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:17:03,161 >> {'loss': 1.5733, 'grad_norm': 0.2190556824207306, 'learning_rate': 4.4113514698014955e-06, 'epoch': 0.62, 'num_input_tokens_seen': 3250585581, 'completed': '62.00% (775 / 1_250)', 'remaining time': '4:35:33', 'throughput': '132570.53', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:17:38,522 >> {'loss': 1.6226, 'grad_norm': 0.22638893127441406, 'learning_rate': 4.399162634696918e-06, 'epoch': 0.6208, 'num_input_tokens_seen': 3254779885, 'completed': '62.08% (776 / 1_250)', 'remaining time': '4:34:58', 'throughput': '118614.65', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:18:13,573 >> {'loss': 1.3847, 'grad_norm': 0.2706611752510071, 'learning_rate': 4.386982384143248e-06, 'epoch': 0.6216, 'num_input_tokens_seen': 3258974189, 'completed': '62.16% (777 / 1_250)', 'remaining time': '4:34:24', 'throughput': '119660.87', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:18:48,252 >> {'loss': 1.6827, 'grad_norm': 0.309236615896225, 'learning_rate': 4.374810813124532e-06, 'epoch': 0.6224, 'num_input_tokens_seen': 3263168493, 'completed': '62.24% (778 / 1_250)', 'remaining time': '4:33:49', 'throughput': '120947.64', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:19:19,860 >> {'loss': 1.684, 'grad_norm': 0.24962997436523438, 'learning_rate': 4.362648016557118e-06, 'epoch': 0.6232, 'num_input_tokens_seen': 3267362797, 'completed': '62.32% (779 / 1_250)', 'remaining time': '4:33:12', 'throughput': '132695.75', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:19:50,826 >> {'loss': 1.7052, 'grad_norm': 0.24443963170051575, 'learning_rate': 4.3504940892889434e-06, 'epoch': 0.624, 'num_input_tokens_seen': 3271557101, 'completed': '62.40% (780 / 1_250)', 'remaining time': '4:32:35', 'throughput': '135448.60', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:20:25,980 >> {'loss': 1.6359, 'grad_norm': 0.1958724409341812, 'learning_rate': 4.338349126098771e-06, 'epoch': 0.6248, 'num_input_tokens_seen': 3275751405, 'completed': '62.48% (781 / 1_250)', 'remaining time': '4:32:00', 'throughput': '119311.85', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:21:01,287 >> {'loss': 1.7343, 'grad_norm': 0.20847539603710175, 'learning_rate': 4.3262132216954655e-06, 'epoch': 0.6256, 'num_input_tokens_seen': 3279945709, 'completed': '62.56% (782 / 1_250)', 'remaining time': '4:31:26', 'throughput': '118797.42', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:21:36,686 >> {'loss': 1.5184, 'grad_norm': 0.20642276108264923, 'learning_rate': 4.314086470717244e-06, 'epoch': 0.6264, 'num_input_tokens_seen': 3284140013, 'completed': '62.64% (783 / 1_250)', 'remaining time': '4:30:51', 'throughput': '118486.44', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:22:11,112 >> {'loss': 1.5982, 'grad_norm': 0.3149787187576294, 'learning_rate': 4.301968967730951e-06, 'epoch': 0.6272, 'num_input_tokens_seen': 3288334317, 'completed': '62.72% (784 / 1_250)', 'remaining time': '4:30:16', 'throughput': '121833.49', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:22:42,368 >> {'loss': 1.6997, 'grad_norm': 0.18410098552703857, 'learning_rate': 4.289860807231305e-06, 'epoch': 0.628, 'num_input_tokens_seen': 3292528621, 'completed': '62.80% (785 / 1_250)', 'remaining time': '4:29:39', 'throughput': '134192.91', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:23:17,349 >> {'loss': 1.8161, 'grad_norm': 0.25286152958869934, 'learning_rate': 4.277762083640175e-06, 'epoch': 0.6288, 'num_input_tokens_seen': 3296722925, 'completed': '62.88% (786 / 1_250)', 'remaining time': '4:29:05', 'throughput': '119901.60', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:23:52,779 >> {'loss': 1.5986, 'grad_norm': 0.2946303188800812, 'learning_rate': 4.265672891305841e-06, 'epoch': 0.6296, 'num_input_tokens_seen': 3300917228, 'completed': '62.96% (787 / 1_250)', 'remaining time': '4:28:30', 'throughput': '118382.74', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:24:23,531 >> {'loss': 1.6012, 'grad_norm': 0.7601927518844604, 'learning_rate': 4.25359332450225e-06, 'epoch': 0.6304, 'num_input_tokens_seen': 3305111532, 'completed': '63.04% (788 / 1_250)', 'remaining time': '4:27:53', 'throughput': '136394.10', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:24:57,947 >> {'loss': 1.3621, 'grad_norm': 0.5034056901931763, 'learning_rate': 4.241523477428292e-06, 'epoch': 0.6312, 'num_input_tokens_seen': 3309305836, 'completed': '63.12% (789 / 1_250)', 'remaining time': '4:27:18', 'throughput': '121870.18', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:25:33,336 >> {'loss': 1.6846, 'grad_norm': 0.19735828042030334, 'learning_rate': 4.229463444207056e-06, 'epoch': 0.632, 'num_input_tokens_seen': 3313500140, 'completed': '63.20% (790 / 1_250)', 'remaining time': '4:26:44', 'throughput': '118520.30', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:26:08,767 >> {'loss': 1.6089, 'grad_norm': 0.40656358003616333, 'learning_rate': 4.217413318885109e-06, 'epoch': 0.6328, 'num_input_tokens_seen': 3317694444, 'completed': '63.28% (791 / 1_250)', 'remaining time': '4:26:09', 'throughput': '118378.25', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:26:44,205 >> {'loss': 1.4531, 'grad_norm': 0.41209688782691956, 'learning_rate': 4.2053731954317436e-06, 'epoch': 0.6336, 'num_input_tokens_seen': 3321888748, 'completed': '63.36% (792 / 1_250)', 'remaining time': '4:25:35', 'throughput': '118357.85', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:27:15,663 >> {'loss': 1.6508, 'grad_norm': 0.23211032152175903, 'learning_rate': 4.193343167738264e-06, 'epoch': 0.6344, 'num_input_tokens_seen': 3326083052, 'completed': '63.44% (793 / 1_250)', 'remaining time': '4:24:58', 'throughput': '133327.68', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:27:50,936 >> {'loss': 1.6194, 'grad_norm': 0.4989689588546753, 'learning_rate': 4.1813233296172426e-06, 'epoch': 0.6352, 'num_input_tokens_seen': 3330277356, 'completed': '63.52% (794 / 1_250)', 'remaining time': '4:24:24', 'throughput': '118909.52', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:28:26,276 >> {'loss': 1.6947, 'grad_norm': 0.4892938435077667, 'learning_rate': 4.169313774801792e-06, 'epoch': 0.636, 'num_input_tokens_seen': 3334471660, 'completed': '63.60% (795 / 1_250)', 'remaining time': '4:23:49', 'throughput': '118685.89', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:29:01,556 >> {'loss': 1.732, 'grad_norm': 0.6418049931526184, 'learning_rate': 4.157314596944829e-06, 'epoch': 0.6368, 'num_input_tokens_seen': 3338665964, 'completed': '63.68% (796 / 1_250)', 'remaining time': '4:23:15', 'throughput': '118884.17', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:29:37,110 >> {'loss': 1.5559, 'grad_norm': 0.5000516772270203, 'learning_rate': 4.145325889618359e-06, 'epoch': 0.6376, 'num_input_tokens_seen': 3342860268, 'completed': '63.76% (797 / 1_250)', 'remaining time': '4:22:40', 'throughput': '117972.80', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:30:12,731 >> {'loss': 1.778, 'grad_norm': 0.400610089302063, 'learning_rate': 4.133347746312727e-06, 'epoch': 0.6384, 'num_input_tokens_seen': 3347054572, 'completed': '63.84% (798 / 1_250)', 'remaining time': '4:22:06', 'throughput': '117748.00', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:30:47,786 >> {'loss': 1.7254, 'grad_norm': 0.5072852373123169, 'learning_rate': 4.121380260435898e-06, 'epoch': 0.6392, 'num_input_tokens_seen': 3351248876, 'completed': '63.92% (799 / 1_250)', 'remaining time': '4:21:31', 'throughput': '119647.22', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:31:22,294 >> {'loss': 1.7498, 'grad_norm': 0.362869530916214, 'learning_rate': 4.109423525312738e-06, 'epoch': 0.64, 'num_input_tokens_seen': 3355443180, 'completed': '64.00% (800 / 1_250)', 'remaining time': '4:20:56', 'throughput': '121547.81', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:31:56,825 >> {'loss': 1.5385, 'grad_norm': 0.23903866112232208, 'learning_rate': 4.097477634184263e-06, 'epoch': 0.6408, 'num_input_tokens_seen': 3359637484, 'completed': '64.08% (801 / 1_250)', 'remaining time': '4:20:21', 'throughput': '121464.68', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:32:28,103 >> {'loss': 1.6831, 'grad_norm': 0.3433187007904053, 'learning_rate': 4.0855426802069335e-06, 'epoch': 0.6416, 'num_input_tokens_seen': 3363831788, 'completed': '64.16% (802 / 1_250)', 'remaining time': '4:19:45', 'throughput': '134094.33', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:33:03,541 >> {'loss': 1.6673, 'grad_norm': 0.3008342981338501, 'learning_rate': 4.073618756451917e-06, 'epoch': 0.6424, 'num_input_tokens_seen': 3368026092, 'completed': '64.24% (803 / 1_250)', 'remaining time': '4:19:10', 'throughput': '118357.56', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:33:39,149 >> {'loss': 1.502, 'grad_norm': 0.4870845377445221, 'learning_rate': 4.06170595590437e-06, 'epoch': 0.6432, 'num_input_tokens_seen': 3372220396, 'completed': '64.32% (804 / 1_250)', 'remaining time': '4:18:36', 'throughput': '117789.88', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:34:12,720 >> {'loss': 1.6064, 'grad_norm': 0.21784792840480804, 'learning_rate': 4.0498043714627015e-06, 'epoch': 0.644, 'num_input_tokens_seen': 3376414700, 'completed': '64.40% (805 / 1_250)', 'remaining time': '4:18:00', 'throughput': '124938.96', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:34:48,254 >> {'loss': 1.6495, 'grad_norm': 0.25253498554229736, 'learning_rate': 4.037914095937857e-06, 'epoch': 0.6448, 'num_input_tokens_seen': 3380609004, 'completed': '64.48% (806 / 1_250)', 'remaining time': '4:17:26', 'throughput': '118037.94', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:35:23,733 >> {'loss': 1.5589, 'grad_norm': 0.2710424065589905, 'learning_rate': 4.026035222052594e-06, 'epoch': 0.6456, 'num_input_tokens_seen': 3384803308, 'completed': '64.56% (807 / 1_250)', 'remaining time': '4:16:52', 'throughput': '118216.93', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:35:59,068 >> {'loss': 1.5582, 'grad_norm': 0.4364379048347473, 'learning_rate': 4.014167842440758e-06, 'epoch': 0.6464, 'num_input_tokens_seen': 3388997612, 'completed': '64.64% (808 / 1_250)', 'remaining time': '4:16:17', 'throughput': '118702.48', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:36:34,191 >> {'loss': 1.5512, 'grad_norm': 0.21274422109127045, 'learning_rate': 4.00231204964656e-06, 'epoch': 0.6472, 'num_input_tokens_seen': 3393191916, 'completed': '64.72% (809 / 1_250)', 'remaining time': '4:15:43', 'throughput': '119418.86', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:37:08,607 >> {'loss': 1.6552, 'grad_norm': 0.6566656231880188, 'learning_rate': 3.990467936123853e-06, 'epoch': 0.648, 'num_input_tokens_seen': 3397386220, 'completed': '64.80% (810 / 1_250)', 'remaining time': '4:15:08', 'throughput': '121870.25', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:37:43,880 >> {'loss': 1.5262, 'grad_norm': 0.17947429418563843, 'learning_rate': 3.978635594235414e-06, 'epoch': 0.6488, 'num_input_tokens_seen': 3401580524, 'completed': '64.88% (811 / 1_250)', 'remaining time': '4:14:33', 'throughput': '118909.10', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:38:19,099 >> {'loss': 1.6743, 'grad_norm': 0.5766887068748474, 'learning_rate': 3.9668151162522185e-06, 'epoch': 0.6496, 'num_input_tokens_seen': 3405774828, 'completed': '64.96% (812 / 1_250)', 'remaining time': '4:13:58', 'throughput': '119093.08', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:38:54,271 >> {'loss': 1.7154, 'grad_norm': 0.544410765171051, 'learning_rate': 3.955006594352732e-06, 'epoch': 0.6504, 'num_input_tokens_seen': 3409969132, 'completed': '65.04% (813 / 1_250)', 'remaining time': '4:13:24', 'throughput': '119251.04', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:39:29,730 >> {'loss': 1.5331, 'grad_norm': 0.35976430773735046, 'learning_rate': 3.94321012062218e-06, 'epoch': 0.6512, 'num_input_tokens_seen': 3414163436, 'completed': '65.12% (814 / 1_250)', 'remaining time': '4:12:49', 'throughput': '118285.51', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:40:03,597 >> {'loss': 1.7192, 'grad_norm': 0.5844708681106567, 'learning_rate': 3.931425787051832e-06, 'epoch': 0.652, 'num_input_tokens_seen': 3418357740, 'completed': '65.20% (815 / 1_250)', 'remaining time': '4:12:14', 'throughput': '123846.25', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:40:38,164 >> {'loss': 1.5226, 'grad_norm': 0.3600381314754486, 'learning_rate': 3.919653685538291e-06, 'epoch': 0.6528, 'num_input_tokens_seen': 3422552044, 'completed': '65.28% (816 / 1_250)', 'remaining time': '4:11:39', 'throughput': '121336.73', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:41:13,488 >> {'loss': 1.6384, 'grad_norm': 0.4271743893623352, 'learning_rate': 3.907893907882768e-06, 'epoch': 0.6536, 'num_input_tokens_seen': 3426746348, 'completed': '65.36% (817 / 1_250)', 'remaining time': '4:11:05', 'throughput': '118739.42', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:41:45,437 >> {'loss': 1.4941, 'grad_norm': 0.48260343074798584, 'learning_rate': 3.896146545790373e-06, 'epoch': 0.6544, 'num_input_tokens_seen': 3430940652, 'completed': '65.44% (818 / 1_250)', 'remaining time': '4:10:28', 'throughput': '131280.66', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:42:19,666 >> {'loss': 1.4472, 'grad_norm': 0.17133843898773193, 'learning_rate': 3.884411690869393e-06, 'epoch': 0.6552, 'num_input_tokens_seen': 3435134956, 'completed': '65.52% (819 / 1_250)', 'remaining time': '4:09:53', 'throughput': '122536.09', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:42:54,888 >> {'loss': 1.6054, 'grad_norm': 0.4271167516708374, 'learning_rate': 3.872689434630585e-06, 'epoch': 0.656, 'num_input_tokens_seen': 3439329260, 'completed': '65.60% (820 / 1_250)', 'remaining time': '4:09:19', 'throughput': '119083.80', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:43:29,988 >> {'loss': 1.4544, 'grad_norm': 0.236142098903656, 'learning_rate': 3.860979868486459e-06, 'epoch': 0.6568, 'num_input_tokens_seen': 3443523564, 'completed': '65.68% (821 / 1_250)', 'remaining time': '4:08:44', 'throughput': '119495.74', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:44:05,319 >> {'loss': 1.5114, 'grad_norm': 0.18624247610569, 'learning_rate': 3.849283083750562e-06, 'epoch': 0.6576, 'num_input_tokens_seen': 3447717868, 'completed': '65.76% (822 / 1_250)', 'remaining time': '4:08:10', 'throughput': '118713.93', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:44:40,351 >> {'loss': 1.7386, 'grad_norm': 0.3094865083694458, 'learning_rate': 3.837599171636773e-06, 'epoch': 0.6584, 'num_input_tokens_seen': 3451912172, 'completed': '65.84% (823 / 1_250)', 'remaining time': '4:07:35', 'throughput': '119728.09', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:45:11,760 >> {'loss': 1.7357, 'grad_norm': 0.27969154715538025, 'learning_rate': 3.825928223258586e-06, 'epoch': 0.6592, 'num_input_tokens_seen': 3456106475, 'completed': '65.92% (824 / 1_250)', 'remaining time': '4:06:58', 'throughput': '133539.12', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:45:47,177 >> {'loss': 1.4635, 'grad_norm': 0.24413318932056427, 'learning_rate': 3.8142703296283954e-06, 'epoch': 0.66, 'num_input_tokens_seen': 3460300779, 'completed': '66.00% (825 / 1_250)', 'remaining time': '4:06:24', 'throughput': '118424.73', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:46:22,623 >> {'loss': 1.5786, 'grad_norm': 0.3017278015613556, 'learning_rate': 3.802625581656807e-06, 'epoch': 0.6608, 'num_input_tokens_seen': 3464495083, 'completed': '66.08% (826 / 1_250)', 'remaining time': '4:05:50', 'throughput': '118329.78', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:46:58,149 >> {'loss': 1.6412, 'grad_norm': 0.26088812947273254, 'learning_rate': 3.7909940701518955e-06, 'epoch': 0.6616, 'num_input_tokens_seen': 3468689387, 'completed': '66.16% (827 / 1_250)', 'remaining time': '4:05:15', 'throughput': '118064.17', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:47:33,492 >> {'loss': 1.5671, 'grad_norm': 0.49284422397613525, 'learning_rate': 3.7793758858185293e-06, 'epoch': 0.6624, 'num_input_tokens_seen': 3472883691, 'completed': '66.24% (828 / 1_250)', 'remaining time': '4:04:41', 'throughput': '118674.48', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:48:08,017 >> {'loss': 1.605, 'grad_norm': 0.2770119905471802, 'learning_rate': 3.7677711192576425e-06, 'epoch': 0.6632, 'num_input_tokens_seen': 3477077995, 'completed': '66.32% (829 / 1_250)', 'remaining time': '4:04:06', 'throughput': '121485.53', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:48:43,339 >> {'loss': 1.4819, 'grad_norm': 0.21008341014385223, 'learning_rate': 3.7561798609655374e-06, 'epoch': 0.664, 'num_input_tokens_seen': 3481272299, 'completed': '66.40% (830 / 1_250)', 'remaining time': '4:03:31', 'throughput': '118742.20', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:49:18,494 >> {'loss': 1.626, 'grad_norm': 0.17199884355068207, 'learning_rate': 3.744602201333172e-06, 'epoch': 0.6648, 'num_input_tokens_seen': 3485466602, 'completed': '66.48% (831 / 1_250)', 'remaining time': '4:02:57', 'throughput': '119310.88', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:49:53,814 >> {'loss': 1.6788, 'grad_norm': 0.19319367408752441, 'learning_rate': 3.7330382306454625e-06, 'epoch': 0.6656, 'num_input_tokens_seen': 3489660906, 'completed': '66.56% (832 / 1_250)', 'remaining time': '4:02:22', 'throughput': '118751.93', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:50:28,856 >> {'loss': 1.6132, 'grad_norm': 0.2874034643173218, 'learning_rate': 3.7214880390805776e-06, 'epoch': 0.6664, 'num_input_tokens_seen': 3493855210, 'completed': '66.64% (833 / 1_250)', 'remaining time': '4:01:47', 'throughput': '119693.14', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:51:01,591 >> {'loss': 1.6631, 'grad_norm': 0.1782878041267395, 'learning_rate': 3.709951716709227e-06, 'epoch': 0.6672, 'num_input_tokens_seen': 3498049513, 'completed': '66.72% (834 / 1_250)', 'remaining time': '4:01:12', 'throughput': '128130.11', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:51:36,800 >> {'loss': 1.5744, 'grad_norm': 0.3311098515987396, 'learning_rate': 3.698429353493974e-06, 'epoch': 0.668, 'num_input_tokens_seen': 3502243817, 'completed': '66.80% (835 / 1_250)', 'remaining time': '4:00:37', 'throughput': '119125.95', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:52:07,675 >> {'loss': 1.7545, 'grad_norm': 0.20420482754707336, 'learning_rate': 3.686921039288519e-06, 'epoch': 0.6688, 'num_input_tokens_seen': 3506438121, 'completed': '66.88% (836 / 1_250)', 'remaining time': '4:00:00', 'throughput': '135846.75', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:52:38,572 >> {'loss': 1.6078, 'grad_norm': 0.2168005108833313, 'learning_rate': 3.6754268638370093e-06, 'epoch': 0.6696, 'num_input_tokens_seen': 3510632425, 'completed': '66.96% (837 / 1_250)', 'remaining time': '3:59:24', 'throughput': '135750.58', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:53:14,087 >> {'loss': 1.5214, 'grad_norm': 0.20597831904888153, 'learning_rate': 3.663946916773333e-06, 'epoch': 0.6704, 'num_input_tokens_seen': 3514826729, 'completed': '67.04% (838 / 1_250)', 'remaining time': '3:58:49', 'throughput': '118098.68', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:53:49,423 >> {'loss': 1.7449, 'grad_norm': 0.20154108107089996, 'learning_rate': 3.6524812876204243e-06, 'epoch': 0.6712, 'num_input_tokens_seen': 3519021033, 'completed': '67.12% (839 / 1_250)', 'remaining time': '3:58:15', 'throughput': '118699.68', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:54:24,813 >> {'loss': 1.6531, 'grad_norm': 0.2799050807952881, 'learning_rate': 3.6410300657895627e-06, 'epoch': 0.672, 'num_input_tokens_seen': 3523215337, 'completed': '67.20% (840 / 1_250)', 'remaining time': '3:57:40', 'throughput': '118516.25', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:55:00,056 >> {'loss': 1.5895, 'grad_norm': 0.3195333480834961, 'learning_rate': 3.6295933405796745e-06, 'epoch': 0.6728, 'num_input_tokens_seen': 3527409641, 'completed': '67.28% (841 / 1_250)', 'remaining time': '3:57:06', 'throughput': '119011.37', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:55:35,305 >> {'loss': 1.5906, 'grad_norm': 0.19443148374557495, 'learning_rate': 3.6181712011766445e-06, 'epoch': 0.6736, 'num_input_tokens_seen': 3531603945, 'completed': '67.36% (842 / 1_250)', 'remaining time': '3:56:31', 'throughput': '118988.44', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:56:09,312 >> {'loss': 1.6848, 'grad_norm': 0.3358490467071533, 'learning_rate': 3.6067637366526055e-06, 'epoch': 0.6744, 'num_input_tokens_seen': 3535798249, 'completed': '67.44% (843 / 1_250)', 'remaining time': '3:55:56', 'throughput': '123337.05', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:56:43,545 >> {'loss': 1.4954, 'grad_norm': 0.20677348971366882, 'learning_rate': 3.5953710359652592e-06, 'epoch': 0.6752, 'num_input_tokens_seen': 3539992553, 'completed': '67.52% (844 / 1_250)', 'remaining time': '3:55:21', 'throughput': '122521.50', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:57:17,485 >> {'loss': 1.6142, 'grad_norm': 0.1968027800321579, 'learning_rate': 3.5839931879571733e-06, 'epoch': 0.676, 'num_input_tokens_seen': 3544186857, 'completed': '67.60% (845 / 1_250)', 'remaining time': '3:54:46', 'throughput': '123582.12', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:57:52,949 >> {'loss': 1.6835, 'grad_norm': 0.23940226435661316, 'learning_rate': 3.572630281355094e-06, 'epoch': 0.6768, 'num_input_tokens_seen': 3548381161, 'completed': '67.68% (846 / 1_250)', 'remaining time': '3:54:11', 'throughput': '118267.49', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:58:28,309 >> {'loss': 1.5496, 'grad_norm': 0.18648038804531097, 'learning_rate': 3.5612824047692497e-06, 'epoch': 0.6776, 'num_input_tokens_seen': 3552575465, 'completed': '67.76% (847 / 1_250)', 'remaining time': '3:53:37', 'throughput': '118617.55', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:59:03,612 >> {'loss': 1.7003, 'grad_norm': 0.27947109937667847, 'learning_rate': 3.5499496466926586e-06, 'epoch': 0.6784, 'num_input_tokens_seen': 3556769769, 'completed': '67.84% (848 / 1_250)', 'remaining time': '3:53:02', 'throughput': '118808.75', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 09:59:35,268 >> {'loss': 1.6431, 'grad_norm': 0.3323851227760315, 'learning_rate': 3.5386320955004473e-06, 'epoch': 0.6792, 'num_input_tokens_seen': 3560964073, 'completed': '67.92% (849 / 1_250)', 'remaining time': '3:52:26', 'throughput': '132497.82', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:00:10,671 >> {'loss': 1.6654, 'grad_norm': 0.22162026166915894, 'learning_rate': 3.527329839449152e-06, 'epoch': 0.68, 'num_input_tokens_seen': 3565158377, 'completed': '68.00% (850 / 1_250)', 'remaining time': '3:51:51', 'throughput': '118474.45', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:00:46,145 >> {'loss': 1.58, 'grad_norm': 0.4386851489543915, 'learning_rate': 3.5160429666760374e-06, 'epoch': 0.6808, 'num_input_tokens_seen': 3569352681, 'completed': '68.08% (851 / 1_250)', 'remaining time': '3:51:17', 'throughput': '118233.85', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:01:21,373 >> {'loss': 1.529, 'grad_norm': 0.2744126319885254, 'learning_rate': 3.5047715651984018e-06, 'epoch': 0.6816, 'num_input_tokens_seen': 3573546985, 'completed': '68.16% (852 / 1_250)', 'remaining time': '3:50:42', 'throughput': '119060.90', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:01:52,131 >> {'loss': 1.6752, 'grad_norm': 0.30578354001045227, 'learning_rate': 3.4935157229129026e-06, 'epoch': 0.6824, 'num_input_tokens_seen': 3577741289, 'completed': '68.24% (853 / 1_250)', 'remaining time': '3:50:06', 'throughput': '136367.12', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:02:23,658 >> {'loss': 1.8385, 'grad_norm': 0.3132741451263428, 'learning_rate': 3.482275527594856e-06, 'epoch': 0.6832, 'num_input_tokens_seen': 3581935593, 'completed': '68.32% (854 / 1_250)', 'remaining time': '3:49:29', 'throughput': '133037.41', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:02:58,796 >> {'loss': 1.7084, 'grad_norm': 0.2605588734149933, 'learning_rate': 3.471051066897563e-06, 'epoch': 0.684, 'num_input_tokens_seen': 3586129897, 'completed': '68.40% (855 / 1_250)', 'remaining time': '3:48:55', 'throughput': '119368.51', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:03:34,270 >> {'loss': 1.7006, 'grad_norm': 0.406504362821579, 'learning_rate': 3.459842428351622e-06, 'epoch': 0.6848, 'num_input_tokens_seen': 3590324201, 'completed': '68.48% (856 / 1_250)', 'remaining time': '3:48:20', 'throughput': '118232.94', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:04:09,551 >> {'loss': 1.6338, 'grad_norm': 0.2476229965686798, 'learning_rate': 3.4486496993642516e-06, 'epoch': 0.6856, 'num_input_tokens_seen': 3594518505, 'completed': '68.56% (857 / 1_250)', 'remaining time': '3:47:46', 'throughput': '118885.40', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:04:44,798 >> {'loss': 1.5541, 'grad_norm': 0.19210600852966309, 'learning_rate': 3.437472967218596e-06, 'epoch': 0.6864, 'num_input_tokens_seen': 3598712809, 'completed': '68.64% (858 / 1_250)', 'remaining time': '3:47:11', 'throughput': '118996.65', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:05:20,094 >> {'loss': 1.5618, 'grad_norm': 0.24849624931812286, 'learning_rate': 3.4263123190730617e-06, 'epoch': 0.6872, 'num_input_tokens_seen': 3602907113, 'completed': '68.72% (859 / 1_250)', 'remaining time': '3:46:37', 'throughput': '118830.37', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:05:55,354 >> {'loss': 1.5665, 'grad_norm': 0.19369983673095703, 'learning_rate': 3.415167841960624e-06, 'epoch': 0.688, 'num_input_tokens_seen': 3607101417, 'completed': '68.80% (860 / 1_250)', 'remaining time': '3:46:02', 'throughput': '118955.64', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:06:26,235 >> {'loss': 1.8917, 'grad_norm': 0.2739676833152771, 'learning_rate': 3.4040396227881513e-06, 'epoch': 0.6888, 'num_input_tokens_seen': 3611295721, 'completed': '68.88% (861 / 1_250)', 'remaining time': '3:45:26', 'throughput': '135819.94', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:07:01,507 >> {'loss': 1.6051, 'grad_norm': 0.16946350038051605, 'learning_rate': 3.3929277483357355e-06, 'epoch': 0.6896, 'num_input_tokens_seen': 3615490025, 'completed': '68.96% (862 / 1_250)', 'remaining time': '3:44:51', 'throughput': '118914.96', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:07:36,930 >> {'loss': 1.5698, 'grad_norm': 0.2855413854122162, 'learning_rate': 3.3818323052560036e-06, 'epoch': 0.6904, 'num_input_tokens_seen': 3619684329, 'completed': '69.04% (863 / 1_250)', 'remaining time': '3:44:17', 'throughput': '118404.82', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:08:09,239 >> {'loss': 1.5309, 'grad_norm': 0.1719910204410553, 'learning_rate': 3.3707533800734516e-06, 'epoch': 0.6912, 'num_input_tokens_seen': 3623878633, 'completed': '69.12% (864 / 1_250)', 'remaining time': '3:43:41', 'throughput': '129819.00', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:08:44,430 >> {'loss': 1.6414, 'grad_norm': 0.17135322093963623, 'learning_rate': 3.3596910591837613e-06, 'epoch': 0.692, 'num_input_tokens_seen': 3628072937, 'completed': '69.20% (865 / 1_250)', 'remaining time': '3:43:06', 'throughput': '119188.24', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:09:19,639 >> {'loss': 1.8217, 'grad_norm': 0.31593239307403564, 'learning_rate': 3.3486454288531354e-06, 'epoch': 0.6928, 'num_input_tokens_seen': 3632267241, 'completed': '69.28% (866 / 1_250)', 'remaining time': '3:42:32', 'throughput': '119124.84', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:09:54,998 >> {'loss': 1.4547, 'grad_norm': 0.20986934006214142, 'learning_rate': 3.337616575217617e-06, 'epoch': 0.6936, 'num_input_tokens_seen': 3636461545, 'completed': '69.36% (867 / 1_250)', 'remaining time': '3:41:57', 'throughput': '118620.39', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:10:29,949 >> {'loss': 1.5499, 'grad_norm': 0.21494309604167938, 'learning_rate': 3.3266045842824234e-06, 'epoch': 0.6944, 'num_input_tokens_seen': 3640655849, 'completed': '69.44% (868 / 1_250)', 'remaining time': '3:41:22', 'throughput': '120006.46', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:11:05,317 >> {'loss': 1.4072, 'grad_norm': 0.1983976513147354, 'learning_rate': 3.3156095419212676e-06, 'epoch': 0.6952, 'num_input_tokens_seen': 3644850153, 'completed': '69.52% (869 / 1_250)', 'remaining time': '3:40:48', 'throughput': '118589.09', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:11:40,732 >> {'loss': 1.5416, 'grad_norm': 0.22488193213939667, 'learning_rate': 3.304631533875703e-06, 'epoch': 0.696, 'num_input_tokens_seen': 3649044457, 'completed': '69.60% (870 / 1_250)', 'remaining time': '3:40:13', 'throughput': '118433.86', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:12:15,550 >> {'loss': 1.6983, 'grad_norm': 0.19367365539073944, 'learning_rate': 3.293670645754441e-06, 'epoch': 0.6968, 'num_input_tokens_seen': 3653238761, 'completed': '69.68% (871 / 1_250)', 'remaining time': '3:39:39', 'throughput': '120460.84', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:12:51,049 >> {'loss': 1.6657, 'grad_norm': 0.17963242530822754, 'learning_rate': 3.2827269630326887e-06, 'epoch': 0.6976, 'num_input_tokens_seen': 3657433065, 'completed': '69.76% (872 / 1_250)', 'remaining time': '3:39:04', 'throughput': '118154.24', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:13:24,558 >> {'loss': 1.5523, 'grad_norm': 0.21495884656906128, 'learning_rate': 3.271800571051482e-06, 'epoch': 0.6984, 'num_input_tokens_seen': 3661627369, 'completed': '69.84% (873 / 1_250)', 'remaining time': '3:38:29', 'throughput': '125168.79', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:14:00,051 >> {'loss': 1.7333, 'grad_norm': 0.18423007428646088, 'learning_rate': 3.260891555017019e-06, 'epoch': 0.6992, 'num_input_tokens_seen': 3665821673, 'completed': '69.92% (874 / 1_250)', 'remaining time': '3:37:54', 'throughput': '118174.09', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:14:35,679 >> {'loss': 1.5618, 'grad_norm': 0.18177147209644318, 'learning_rate': 3.2500000000000015e-06, 'epoch': 0.7, 'num_input_tokens_seen': 3670015977, 'completed': '70.00% (875 / 1_250)', 'remaining time': '3:37:20', 'throughput': '117723.72', 'gpu_mem_free': '16314MB'} +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:689: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +[INFO|trainer.py:3503] 2026-05-02 10:14:44,269 >> Saving model checkpoint to /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-875 +[INFO|configuration_utils.py:472] 2026-05-02 10:14:44,270 >> Configuration saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-875/config.json +[INFO|configuration_utils.py:807] 2026-05-02 10:14:44,270 >> Configuration saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-875/generation_config.json +[INFO|modeling_utils.py:2807] 2026-05-02 10:14:56,901 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 3 checkpoint shards. You can find where each parameters has been saved in the index located at /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-875/model.safetensors.index.json. +[INFO|tokenization_utils_base.py:2684] 2026-05-02 10:14:56,904 >> tokenizer config file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-875/tokenizer_config.json +[INFO|tokenization_utils_base.py:2693] 2026-05-02 10:14:56,904 >> Special tokens file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-875/special_tokens_map.json +[INFO|tokenization_utils_base.py:2684] 2026-05-02 10:15:06,872 >> tokenizer config file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/tokenizer_config.json +[INFO|tokenization_utils_base.py:2693] 2026-05-02 10:15:06,872 >> Special tokens file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/special_tokens_map.json +[INFO|trainer.py:3595] 2026-05-02 10:15:06,885 >> Deleting older checkpoint [/tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-750] due to args.save_total_limit +[WARNING|trainer.py:870] 2026-05-02 10:15:08,105 >> Save streaming dataset state: {'epoch': 0, 'sample_in_epoch': 224000, 'num_canonical_nodes': 2, 'shuffle_seed': 42, 'initial_physical_nodes': 2} +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/utils/checkpoint.py:1399: FutureWarning: `torch.cpu.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cpu', args...)` instead. + with device_autocast_ctx, torch.cpu.amp.autocast(**cpu_autocast_kwargs), recompute_context: # type: ignore[attr-defined] +[INFO|trainer.py:175] 2026-05-02 10:15:43,605 >> {'loss': 1.5505, 'grad_norm': 0.2207580953836441, 'learning_rate': 3.2391259909349593e-06, 'epoch': 0.7008, 'num_input_tokens_seen': 3674210281, 'completed': '70.08% (876 / 1_250)', 'remaining time': '3:36:59', 'throughput': '61747.84', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:16:18,831 >> {'loss': 1.7375, 'grad_norm': 0.21986721456050873, 'learning_rate': 3.2282696126196033e-06, 'epoch': 0.7016, 'num_input_tokens_seen': 3678404584, 'completed': '70.16% (877 / 1_250)', 'remaining time': '3:36:25', 'throughput': '119069.19', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:16:54,041 >> {'loss': 1.581, 'grad_norm': 0.20181365311145782, 'learning_rate': 3.2174309497141494e-06, 'epoch': 0.7024, 'num_input_tokens_seen': 3682598888, 'completed': '70.24% (878 / 1_250)', 'remaining time': '3:35:50', 'throughput': '119122.25', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:17:29,082 >> {'loss': 1.4933, 'grad_norm': 0.23399141430854797, 'learning_rate': 3.20661008674067e-06, 'epoch': 0.7032, 'num_input_tokens_seen': 3686793192, 'completed': '70.32% (879 / 1_250)', 'remaining time': '3:35:15', 'throughput': '119698.28', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:18:03,621 >> {'loss': 1.5519, 'grad_norm': 0.2009698897600174, 'learning_rate': 3.1958071080824293e-06, 'epoch': 0.704, 'num_input_tokens_seen': 3690987496, 'completed': '70.40% (880 / 1_250)', 'remaining time': '3:34:40', 'throughput': '121437.37', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:18:39,000 >> {'loss': 1.5934, 'grad_norm': 0.25586992502212524, 'learning_rate': 3.1850220979832215e-06, 'epoch': 0.7048, 'num_input_tokens_seen': 3695181800, 'completed': '70.48% (881 / 1_250)', 'remaining time': '3:34:06', 'throughput': '118551.28', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:19:13,239 >> {'loss': 1.9243, 'grad_norm': 0.30244016647338867, 'learning_rate': 3.1742551405467248e-06, 'epoch': 0.7056, 'num_input_tokens_seen': 3699376103, 'completed': '70.56% (882 / 1_250)', 'remaining time': '3:33:31', 'throughput': '122501.49', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:19:48,601 >> {'loss': 1.5876, 'grad_norm': 0.18862999975681305, 'learning_rate': 3.163506319735834e-06, 'epoch': 0.7064, 'num_input_tokens_seen': 3703570407, 'completed': '70.64% (883 / 1_250)', 'remaining time': '3:32:56', 'throughput': '118610.30', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:20:23,809 >> {'loss': 1.5119, 'grad_norm': 0.19005031883716583, 'learning_rate': 3.1527757193720154e-06, 'epoch': 0.7072, 'num_input_tokens_seen': 3707764711, 'completed': '70.72% (884 / 1_250)', 'remaining time': '3:32:22', 'throughput': '119131.63', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:20:59,263 >> {'loss': 1.3975, 'grad_norm': 0.237460657954216, 'learning_rate': 3.1420634231346447e-06, 'epoch': 0.708, 'num_input_tokens_seen': 3711959015, 'completed': '70.80% (885 / 1_250)', 'remaining time': '3:31:47', 'throughput': '118302.55', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:21:34,594 >> {'loss': 1.7782, 'grad_norm': 0.182357057929039, 'learning_rate': 3.1313695145603605e-06, 'epoch': 0.7088, 'num_input_tokens_seen': 3716153319, 'completed': '70.88% (886 / 1_250)', 'remaining time': '3:31:12', 'throughput': '118712.37', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:22:09,992 >> {'loss': 1.5396, 'grad_norm': 0.24649469554424286, 'learning_rate': 3.1206940770424076e-06, 'epoch': 0.7096, 'num_input_tokens_seen': 3720347623, 'completed': '70.96% (887 / 1_250)', 'remaining time': '3:30:38', 'throughput': '118489.99', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:22:44,120 >> {'loss': 1.5384, 'grad_norm': 0.15874087810516357, 'learning_rate': 3.1100371938299966e-06, 'epoch': 0.7104, 'num_input_tokens_seen': 3724541927, 'completed': '71.04% (888 / 1_250)', 'remaining time': '3:30:03', 'throughput': '122901.13', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:23:19,733 >> {'loss': 1.6337, 'grad_norm': 0.43665626645088196, 'learning_rate': 3.0993989480276386e-06, 'epoch': 0.7112, 'num_input_tokens_seen': 3728736231, 'completed': '71.12% (889 / 1_250)', 'remaining time': '3:29:28', 'throughput': '117773.18', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:23:51,340 >> {'loss': 1.7611, 'grad_norm': 0.413664847612381, 'learning_rate': 3.0887794225945143e-06, 'epoch': 0.712, 'num_input_tokens_seen': 3732930534, 'completed': '71.20% (890 / 1_250)', 'remaining time': '3:28:52', 'throughput': '132703.94', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:24:25,643 >> {'loss': 1.5457, 'grad_norm': 0.2584073543548584, 'learning_rate': 3.078178700343818e-06, 'epoch': 0.7128, 'num_input_tokens_seen': 3737124838, 'completed': '71.28% (891 / 1_250)', 'remaining time': '3:28:17', 'throughput': '122270.18', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:25:00,155 >> {'loss': 1.5382, 'grad_norm': 0.30275869369506836, 'learning_rate': 3.0675968639421084e-06, 'epoch': 0.7136, 'num_input_tokens_seen': 3741319142, 'completed': '71.36% (892 / 1_250)', 'remaining time': '3:27:42', 'throughput': '121532.28', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:25:33,090 >> {'loss': 1.6342, 'grad_norm': 0.36054056882858276, 'learning_rate': 3.0570339959086727e-06, 'epoch': 0.7144, 'num_input_tokens_seen': 3745513445, 'completed': '71.44% (893 / 1_250)', 'remaining time': '3:27:07', 'throughput': '127352.30', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:26:08,780 >> {'loss': 1.8135, 'grad_norm': 0.1815565824508667, 'learning_rate': 3.046490178614875e-06, 'epoch': 0.7152, 'num_input_tokens_seen': 3749707749, 'completed': '71.52% (894 / 1_250)', 'remaining time': '3:26:32', 'throughput': '117519.64', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:26:44,017 >> {'loss': 1.5514, 'grad_norm': 0.35312092304229736, 'learning_rate': 3.035965494283525e-06, 'epoch': 0.716, 'num_input_tokens_seen': 3753902053, 'completed': '71.60% (895 / 1_250)', 'remaining time': '3:25:58', 'throughput': '119031.69', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:27:19,273 >> {'loss': 1.7351, 'grad_norm': 0.2797375023365021, 'learning_rate': 3.0254600249882214e-06, 'epoch': 0.7168, 'num_input_tokens_seen': 3758096357, 'completed': '71.68% (896 / 1_250)', 'remaining time': '3:25:23', 'throughput': '118965.15', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:27:54,335 >> {'loss': 1.6668, 'grad_norm': 0.1744924932718277, 'learning_rate': 3.0149738526527265e-06, 'epoch': 0.7176, 'num_input_tokens_seen': 3762290661, 'completed': '71.76% (897 / 1_250)', 'remaining time': '3:24:48', 'throughput': '119627.03', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:28:25,587 >> {'loss': 1.7608, 'grad_norm': 0.3724423348903656, 'learning_rate': 3.004507059050319e-06, 'epoch': 0.7184, 'num_input_tokens_seen': 3766484965, 'completed': '71.84% (898 / 1_250)', 'remaining time': '3:24:12', 'throughput': '134210.48', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:29:01,220 >> {'loss': 1.4714, 'grad_norm': 0.1950729787349701, 'learning_rate': 2.994059725803156e-06, 'epoch': 0.7192, 'num_input_tokens_seen': 3770679269, 'completed': '71.92% (899 / 1_250)', 'remaining time': '3:23:38', 'throughput': '117706.53', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:29:36,500 >> {'loss': 1.465, 'grad_norm': 0.2767573595046997, 'learning_rate': 2.98363193438164e-06, 'epoch': 0.72, 'num_input_tokens_seen': 3774873573, 'completed': '72.00% (900 / 1_250)', 'remaining time': '3:23:03', 'throughput': '118887.57', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:30:11,753 >> {'loss': 1.6793, 'grad_norm': 0.2466665357351303, 'learning_rate': 2.9732237661037855e-06, 'epoch': 0.7208, 'num_input_tokens_seen': 3779067877, 'completed': '72.08% (901 / 1_250)', 'remaining time': '3:22:28', 'throughput': '118976.62', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:30:47,100 >> {'loss': 1.696, 'grad_norm': 0.2339164763689041, 'learning_rate': 2.96283530213458e-06, 'epoch': 0.7216, 'num_input_tokens_seen': 3783262181, 'completed': '72.16% (902 / 1_250)', 'remaining time': '3:21:54', 'throughput': '118662.00', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:31:22,381 >> {'loss': 1.7426, 'grad_norm': 0.3864482045173645, 'learning_rate': 2.9524666234853493e-06, 'epoch': 0.7224, 'num_input_tokens_seen': 3787456485, 'completed': '72.24% (903 / 1_250)', 'remaining time': '3:21:19', 'throughput': '118882.44', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:31:57,770 >> {'loss': 1.5563, 'grad_norm': 0.17779365181922913, 'learning_rate': 2.942117811013139e-06, 'epoch': 0.7232, 'num_input_tokens_seen': 3791650788, 'completed': '72.32% (904 / 1_250)', 'remaining time': '3:20:44', 'throughput': '118518.31', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:32:33,120 >> {'loss': 1.6515, 'grad_norm': 0.28721851110458374, 'learning_rate': 2.931788945420058e-06, 'epoch': 0.724, 'num_input_tokens_seen': 3795845091, 'completed': '72.40% (905 / 1_250)', 'remaining time': '3:20:10', 'throughput': '118651.70', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:33:08,668 >> {'loss': 1.4583, 'grad_norm': 0.23494133353233337, 'learning_rate': 2.921480107252683e-06, 'epoch': 0.7248, 'num_input_tokens_seen': 3800039395, 'completed': '72.48% (906 / 1_250)', 'remaining time': '3:19:35', 'throughput': '117988.43', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:33:39,283 >> {'loss': 1.4647, 'grad_norm': 0.17114321887493134, 'learning_rate': 2.9111913769013987e-06, 'epoch': 0.7256, 'num_input_tokens_seen': 3804233699, 'completed': '72.56% (907 / 1_250)', 'remaining time': '3:18:59', 'throughput': '137002.27', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:34:10,597 >> {'loss': 1.7844, 'grad_norm': 0.35054337978363037, 'learning_rate': 2.900922834599797e-06, 'epoch': 0.7264, 'num_input_tokens_seen': 3808428003, 'completed': '72.64% (908 / 1_250)', 'remaining time': '3:18:23', 'throughput': '133942.91', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:34:45,591 >> {'loss': 1.6509, 'grad_norm': 0.24733752012252808, 'learning_rate': 2.8906745604240287e-06, 'epoch': 0.7272, 'num_input_tokens_seen': 3812622307, 'completed': '72.72% (909 / 1_250)', 'remaining time': '3:17:48', 'throughput': '119859.68', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:35:21,066 >> {'loss': 1.6435, 'grad_norm': 0.32321104407310486, 'learning_rate': 2.880446634292199e-06, 'epoch': 0.728, 'num_input_tokens_seen': 3816816611, 'completed': '72.80% (910 / 1_250)', 'remaining time': '3:17:13', 'throughput': '118233.05', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:35:56,024 >> {'loss': 1.6039, 'grad_norm': 0.28859344124794006, 'learning_rate': 2.870239135963726e-06, 'epoch': 0.7288, 'num_input_tokens_seen': 3821010915, 'completed': '72.88% (911 / 1_250)', 'remaining time': '3:16:39', 'throughput': '119979.88', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:36:31,520 >> {'loss': 1.5553, 'grad_norm': 0.20648641884326935, 'learning_rate': 2.8600521450387347e-06, 'epoch': 0.7296, 'num_input_tokens_seen': 3825205219, 'completed': '72.96% (912 / 1_250)', 'remaining time': '3:16:04', 'throughput': '118162.99', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:37:02,951 >> {'loss': 1.72, 'grad_norm': 0.35594624280929565, 'learning_rate': 2.8498857409574267e-06, 'epoch': 0.7304, 'num_input_tokens_seen': 3829399523, 'completed': '73.04% (913 / 1_250)', 'remaining time': '3:15:28', 'throughput': '133443.64', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:37:35,429 >> {'loss': 1.5668, 'grad_norm': 0.3144766390323639, 'learning_rate': 2.8397400029994613e-06, 'epoch': 0.7312, 'num_input_tokens_seen': 3833593827, 'completed': '73.12% (914 / 1_250)', 'remaining time': '3:14:52', 'throughput': '129141.72', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:38:08,881 >> {'loss': 1.6369, 'grad_norm': 0.3429067134857178, 'learning_rate': 2.8296150102833444e-06, 'epoch': 0.732, 'num_input_tokens_seen': 3837788131, 'completed': '73.20% (915 / 1_250)', 'remaining time': '3:14:17', 'throughput': '125384.97', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:38:41,929 >> {'loss': 1.7108, 'grad_norm': 0.35875096917152405, 'learning_rate': 2.819510841765799e-06, 'epoch': 0.7328, 'num_input_tokens_seen': 3841982435, 'completed': '73.28% (916 / 1_250)', 'remaining time': '3:13:42', 'throughput': '126915.52', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:39:17,472 >> {'loss': 1.4827, 'grad_norm': 0.18347586691379547, 'learning_rate': 2.809427576241167e-06, 'epoch': 0.7336, 'num_input_tokens_seen': 3846176739, 'completed': '73.36% (917 / 1_250)', 'remaining time': '3:13:07', 'throughput': '118004.88', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:39:49,692 >> {'loss': 1.8078, 'grad_norm': 0.22688202559947968, 'learning_rate': 2.7993652923407712e-06, 'epoch': 0.7344, 'num_input_tokens_seen': 3850371043, 'completed': '73.44% (918 / 1_250)', 'remaining time': '3:12:31', 'throughput': '130177.62', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:40:25,170 >> {'loss': 1.4462, 'grad_norm': 0.22539293766021729, 'learning_rate': 2.7893240685323274e-06, 'epoch': 0.7352, 'num_input_tokens_seen': 3854565347, 'completed': '73.52% (919 / 1_250)', 'remaining time': '3:11:57', 'throughput': '118224.88', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:40:56,509 >> {'loss': 1.5979, 'grad_norm': 0.21817539632320404, 'learning_rate': 2.7793039831193134e-06, 'epoch': 0.736, 'num_input_tokens_seen': 3858759651, 'completed': '73.60% (920 / 1_250)', 'remaining time': '3:11:21', 'throughput': '133832.92', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:41:31,850 >> {'loss': 1.5797, 'grad_norm': 0.3295662999153137, 'learning_rate': 2.7693051142403698e-06, 'epoch': 0.7368, 'num_input_tokens_seen': 3862953955, 'completed': '73.68% (921 / 1_250)', 'remaining time': '3:10:46', 'throughput': '118681.80', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:42:07,066 >> {'loss': 1.5654, 'grad_norm': 0.42665740847587585, 'learning_rate': 2.7593275398686857e-06, 'epoch': 0.7376, 'num_input_tokens_seen': 3867148259, 'completed': '73.76% (922 / 1_250)', 'remaining time': '3:10:12', 'throughput': '119102.75', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:42:38,428 >> {'loss': 1.6651, 'grad_norm': 0.21464839577674866, 'learning_rate': 2.7493713378113885e-06, 'epoch': 0.7384, 'num_input_tokens_seen': 3871342563, 'completed': '73.84% (923 / 1_250)', 'remaining time': '3:09:36', 'throughput': '133737.26', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:43:13,844 >> {'loss': 1.7956, 'grad_norm': 0.27561137080192566, 'learning_rate': 2.739436585708942e-06, 'epoch': 0.7392, 'num_input_tokens_seen': 3875536867, 'completed': '73.92% (924 / 1_250)', 'remaining time': '3:09:01', 'throughput': '118430.92', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:43:48,508 >> {'loss': 1.5697, 'grad_norm': 0.17626908421516418, 'learning_rate': 2.7295233610345384e-06, 'epoch': 0.74, 'num_input_tokens_seen': 3879731171, 'completed': '74.00% (925 / 1_250)', 'remaining time': '3:08:26', 'throughput': '120998.73', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:44:23,806 >> {'loss': 1.6283, 'grad_norm': 0.17475782334804535, 'learning_rate': 2.7196317410934964e-06, 'epoch': 0.7408, 'num_input_tokens_seen': 3883925475, 'completed': '74.08% (926 / 1_250)', 'remaining time': '3:07:52', 'throughput': '118826.87', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:44:55,176 >> {'loss': 1.8301, 'grad_norm': 0.20250609517097473, 'learning_rate': 2.7097618030226534e-06, 'epoch': 0.7416, 'num_input_tokens_seen': 3888119779, 'completed': '74.16% (927 / 1_250)', 'remaining time': '3:07:16', 'throughput': '133700.38', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:45:30,559 >> {'loss': 1.5969, 'grad_norm': 0.16977304220199585, 'learning_rate': 2.6999136237897716e-06, 'epoch': 0.7424, 'num_input_tokens_seen': 3892314083, 'completed': '74.24% (928 / 1_250)', 'remaining time': '3:06:41', 'throughput': '118542.36', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:46:05,279 >> {'loss': 1.7354, 'grad_norm': 0.36350762844085693, 'learning_rate': 2.6900872801929303e-06, 'epoch': 0.7432, 'num_input_tokens_seen': 3896508387, 'completed': '74.32% (929 / 1_250)', 'remaining time': '3:06:06', 'throughput': '120803.37', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:46:40,895 >> {'loss': 1.5524, 'grad_norm': 0.2240678369998932, 'learning_rate': 2.68028284885993e-06, 'epoch': 0.744, 'num_input_tokens_seen': 3900702691, 'completed': '74.40% (930 / 1_250)', 'remaining time': '3:05:32', 'throughput': '117765.26', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:47:15,900 >> {'loss': 1.5697, 'grad_norm': 0.28327202796936035, 'learning_rate': 2.6705004062476937e-06, 'epoch': 0.7448, 'num_input_tokens_seen': 3904896994, 'completed': '74.48% (931 / 1_250)', 'remaining time': '3:04:57', 'throughput': '119819.43', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:47:51,305 >> {'loss': 1.6363, 'grad_norm': 0.16952450573444366, 'learning_rate': 2.6607400286416767e-06, 'epoch': 0.7456, 'num_input_tokens_seen': 3909091298, 'completed': '74.56% (932 / 1_250)', 'remaining time': '3:04:22', 'throughput': '118465.90', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:48:26,552 >> {'loss': 1.6404, 'grad_norm': 0.25492218136787415, 'learning_rate': 2.6510017921552656e-06, 'epoch': 0.7464, 'num_input_tokens_seen': 3913285602, 'completed': '74.64% (933 / 1_250)', 'remaining time': '3:03:48', 'throughput': '118999.01', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:49:00,565 >> {'loss': 1.6802, 'grad_norm': 0.3494386076927185, 'learning_rate': 2.6412857727291807e-06, 'epoch': 0.7472, 'num_input_tokens_seen': 3917479906, 'completed': '74.72% (934 / 1_250)', 'remaining time': '3:03:13', 'throughput': '123313.72', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:49:36,156 >> {'loss': 1.5554, 'grad_norm': 0.21151520311832428, 'learning_rate': 2.6315920461308963e-06, 'epoch': 0.748, 'num_input_tokens_seen': 3921674210, 'completed': '74.80% (935 / 1_250)', 'remaining time': '3:02:38', 'throughput': '117847.56', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:50:09,682 >> {'loss': 1.7393, 'grad_norm': 0.47543537616729736, 'learning_rate': 2.6219206879540395e-06, 'epoch': 0.7488, 'num_input_tokens_seen': 3925868514, 'completed': '74.88% (936 / 1_250)', 'remaining time': '3:02:03', 'throughput': '125106.45', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:50:41,814 >> {'loss': 1.6709, 'grad_norm': 0.17675001919269562, 'learning_rate': 2.6122717736178038e-06, 'epoch': 0.7496, 'num_input_tokens_seen': 3930062818, 'completed': '74.96% (937 / 1_250)', 'remaining time': '3:01:27', 'throughput': '130533.00', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:51:17,146 >> {'loss': 1.6508, 'grad_norm': 0.2827574908733368, 'learning_rate': 2.6026453783663586e-06, 'epoch': 0.7504, 'num_input_tokens_seen': 3934257122, 'completed': '75.04% (938 / 1_250)', 'remaining time': '3:00:53', 'throughput': '118710.97', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:51:51,414 >> {'loss': 1.5382, 'grad_norm': 0.2437610924243927, 'learning_rate': 2.5930415772682726e-06, 'epoch': 0.7512, 'num_input_tokens_seen': 3938451426, 'completed': '75.12% (939 / 1_250)', 'remaining time': '3:00:18', 'throughput': '122396.63', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:52:26,591 >> {'loss': 1.4901, 'grad_norm': 0.2301221340894699, 'learning_rate': 2.583460445215911e-06, 'epoch': 0.752, 'num_input_tokens_seen': 3942645730, 'completed': '75.20% (940 / 1_250)', 'remaining time': '2:59:43', 'throughput': '119233.59', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:52:58,704 >> {'loss': 1.6735, 'grad_norm': 0.413441926240921, 'learning_rate': 2.5739020569248696e-06, 'epoch': 0.7528, 'num_input_tokens_seen': 3946840034, 'completed': '75.28% (941 / 1_250)', 'remaining time': '2:59:07', 'throughput': '130612.76', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:53:34,096 >> {'loss': 1.4761, 'grad_norm': 0.1573828011751175, 'learning_rate': 2.564366486933382e-06, 'epoch': 0.7536, 'num_input_tokens_seen': 3951034338, 'completed': '75.36% (942 / 1_250)', 'remaining time': '2:58:33', 'throughput': '118509.34', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:54:09,516 >> {'loss': 1.5805, 'grad_norm': 0.269328773021698, 'learning_rate': 2.554853809601734e-06, 'epoch': 0.7544, 'num_input_tokens_seen': 3955228642, 'completed': '75.44% (943 / 1_250)', 'remaining time': '2:57:58', 'throughput': '118415.84', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:54:44,652 >> {'loss': 1.5131, 'grad_norm': 0.29687055945396423, 'learning_rate': 2.5453640991116967e-06, 'epoch': 0.7552, 'num_input_tokens_seen': 3959422946, 'completed': '75.52% (944 / 1_250)', 'remaining time': '2:57:24', 'throughput': '119375.06', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:55:20,010 >> {'loss': 1.5314, 'grad_norm': 0.19936490058898926, 'learning_rate': 2.5358974294659376e-06, 'epoch': 0.756, 'num_input_tokens_seen': 3963617250, 'completed': '75.60% (945 / 1_250)', 'remaining time': '2:56:49', 'throughput': '118623.04', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:55:55,313 >> {'loss': 1.5611, 'grad_norm': 0.2739168703556061, 'learning_rate': 2.526453874487451e-06, 'epoch': 0.7568, 'num_input_tokens_seen': 3967811554, 'completed': '75.68% (946 / 1_250)', 'remaining time': '2:56:14', 'throughput': '118807.10', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:56:26,033 >> {'loss': 1.6522, 'grad_norm': 0.33100199699401855, 'learning_rate': 2.5170335078189723e-06, 'epoch': 0.7576, 'num_input_tokens_seen': 3972005858, 'completed': '75.76% (947 / 1_250)', 'remaining time': '2:55:38', 'throughput': '136532.31', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:57:01,291 >> {'loss': 1.4769, 'grad_norm': 0.23038093745708466, 'learning_rate': 2.5076364029224147e-06, 'epoch': 0.7584, 'num_input_tokens_seen': 3976200162, 'completed': '75.84% (948 / 1_250)', 'remaining time': '2:55:04', 'throughput': '118962.02', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:57:36,751 >> {'loss': 1.4174, 'grad_norm': 0.26595553755760193, 'learning_rate': 2.498262633078291e-06, 'epoch': 0.7592, 'num_input_tokens_seen': 3980394466, 'completed': '75.92% (949 / 1_250)', 'remaining time': '2:54:29', 'throughput': '118281.23', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:58:11,556 >> {'loss': 1.6097, 'grad_norm': 0.33590272068977356, 'learning_rate': 2.4889122713851397e-06, 'epoch': 0.76, 'num_input_tokens_seen': 3984588770, 'completed': '76.00% (950 / 1_250)', 'remaining time': '2:53:54', 'throughput': '120511.78', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:58:43,457 >> {'loss': 1.6908, 'grad_norm': 0.2561793029308319, 'learning_rate': 2.4795853907589586e-06, 'epoch': 0.7608, 'num_input_tokens_seen': 3988783074, 'completed': '76.08% (951 / 1_250)', 'remaining time': '2:53:19', 'throughput': '131475.87', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:59:18,031 >> {'loss': 1.4843, 'grad_norm': 0.19536243379116058, 'learning_rate': 2.470282063932638e-06, 'epoch': 0.7616, 'num_input_tokens_seen': 3992977378, 'completed': '76.16% (952 / 1_250)', 'remaining time': '2:52:44', 'throughput': '121312.98', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 10:59:53,438 >> {'loss': 1.5498, 'grad_norm': 0.30550917983055115, 'learning_rate': 2.46100236345539e-06, 'epoch': 0.7624, 'num_input_tokens_seen': 3997171682, 'completed': '76.24% (953 / 1_250)', 'remaining time': '2:52:09', 'throughput': '118461.31', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:00:28,797 >> {'loss': 1.5506, 'grad_norm': 0.3514654040336609, 'learning_rate': 2.451746361692183e-06, 'epoch': 0.7632, 'num_input_tokens_seen': 4001365986, 'completed': '76.32% (954 / 1_250)', 'remaining time': '2:51:35', 'throughput': '118619.72', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:01:04,288 >> {'loss': 1.738, 'grad_norm': 0.22004662454128265, 'learning_rate': 2.442514130823177e-06, 'epoch': 0.764, 'num_input_tokens_seen': 4005560290, 'completed': '76.40% (955 / 1_250)', 'remaining time': '2:51:00', 'throughput': '118179.02', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:01:39,557 >> {'loss': 1.5604, 'grad_norm': 0.38220369815826416, 'learning_rate': 2.4333057428431615e-06, 'epoch': 0.7648, 'num_input_tokens_seen': 4009754594, 'completed': '76.48% (956 / 1_250)', 'remaining time': '2:50:25', 'throughput': '118924.07', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:02:14,888 >> {'loss': 1.6218, 'grad_norm': 0.3372167646884918, 'learning_rate': 2.424121269560999e-06, 'epoch': 0.7656, 'num_input_tokens_seen': 4013948898, 'completed': '76.56% (957 / 1_250)', 'remaining time': '2:49:51', 'throughput': '118714.23', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:02:48,576 >> {'loss': 1.5831, 'grad_norm': 0.18092969059944153, 'learning_rate': 2.4149607825990547e-06, 'epoch': 0.7664, 'num_input_tokens_seen': 4018143202, 'completed': '76.64% (958 / 1_250)', 'remaining time': '2:49:16', 'throughput': '124504.18', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:03:24,126 >> {'loss': 1.5008, 'grad_norm': 0.36501964926719666, 'learning_rate': 2.4058243533926473e-06, 'epoch': 0.7672, 'num_input_tokens_seen': 4022337506, 'completed': '76.72% (959 / 1_250)', 'remaining time': '2:48:41', 'throughput': '117983.71', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:03:59,181 >> {'loss': 1.7211, 'grad_norm': 0.4250304102897644, 'learning_rate': 2.396712053189486e-06, 'epoch': 0.768, 'num_input_tokens_seen': 4026531810, 'completed': '76.80% (960 / 1_250)', 'remaining time': '2:48:06', 'throughput': '119650.91', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:04:34,668 >> {'loss': 1.7119, 'grad_norm': 0.28033944964408875, 'learning_rate': 2.38762395304912e-06, 'epoch': 0.7688, 'num_input_tokens_seen': 4030726114, 'completed': '76.88% (961 / 1_250)', 'remaining time': '2:47:32', 'throughput': '118192.50', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:05:10,277 >> {'loss': 1.5656, 'grad_norm': 0.4242093861103058, 'learning_rate': 2.3785601238423788e-06, 'epoch': 0.7696, 'num_input_tokens_seen': 4034920418, 'completed': '76.96% (962 / 1_250)', 'remaining time': '2:46:57', 'throughput': '117787.58', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:05:44,345 >> {'loss': 1.6226, 'grad_norm': 0.30153602361679077, 'learning_rate': 2.3695206362508215e-06, 'epoch': 0.7704, 'num_input_tokens_seen': 4039114722, 'completed': '77.04% (963 / 1_250)', 'remaining time': '2:46:22', 'throughput': '123114.65', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:06:19,934 >> {'loss': 1.686, 'grad_norm': 0.17774240672588348, 'learning_rate': 2.360505560766192e-06, 'epoch': 0.7712, 'num_input_tokens_seen': 4043309025, 'completed': '77.12% (964 / 1_250)', 'remaining time': '2:45:48', 'throughput': '117853.91', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:06:55,437 >> {'loss': 1.6103, 'grad_norm': 0.3169993460178375, 'learning_rate': 2.3515149676898554e-06, 'epoch': 0.772, 'num_input_tokens_seen': 4047503329, 'completed': '77.20% (965 / 1_250)', 'remaining time': '2:45:13', 'throughput': '118139.39', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:07:30,662 >> {'loss': 1.7328, 'grad_norm': 0.4301537275314331, 'learning_rate': 2.3425489271322673e-06, 'epoch': 0.7728, 'num_input_tokens_seen': 4051697632, 'completed': '77.28% (966 / 1_250)', 'remaining time': '2:44:39', 'throughput': '119072.56', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:08:06,015 >> {'loss': 1.5095, 'grad_norm': 0.17795437574386597, 'learning_rate': 2.33360750901241e-06, 'epoch': 0.7736, 'num_input_tokens_seen': 4055891936, 'completed': '77.36% (967 / 1_250)', 'remaining time': '2:44:04', 'throughput': '118641.39', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:08:41,293 >> {'loss': 1.5258, 'grad_norm': 0.27759379148483276, 'learning_rate': 2.3246907830572587e-06, 'epoch': 0.7744, 'num_input_tokens_seen': 4060086240, 'completed': '77.44% (968 / 1_250)', 'remaining time': '2:43:29', 'throughput': '118892.25', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:09:16,568 >> {'loss': 1.6301, 'grad_norm': 0.41011086106300354, 'learning_rate': 2.3157988188012327e-06, 'epoch': 0.7752, 'num_input_tokens_seen': 4064280544, 'completed': '77.52% (969 / 1_250)', 'remaining time': '2:42:55', 'throughput': '118901.63', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:09:51,903 >> {'loss': 1.7319, 'grad_norm': 0.22766470909118652, 'learning_rate': 2.306931685585657e-06, 'epoch': 0.776, 'num_input_tokens_seen': 4068474848, 'completed': '77.60% (970 / 1_250)', 'remaining time': '2:42:20', 'throughput': '118700.11', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:10:26,492 >> {'loss': 1.8086, 'grad_norm': 0.3570314347743988, 'learning_rate': 2.2980894525582162e-06, 'epoch': 0.7768, 'num_input_tokens_seen': 4072669152, 'completed': '77.68% (971 / 1_250)', 'remaining time': '2:41:45', 'throughput': '121262.52', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:11:01,974 >> {'loss': 1.3832, 'grad_norm': 0.3129422962665558, 'learning_rate': 2.2892721886724207e-06, 'epoch': 0.7776, 'num_input_tokens_seen': 4076863456, 'completed': '77.76% (972 / 1_250)', 'remaining time': '2:41:11', 'throughput': '118210.14', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:11:37,560 >> {'loss': 1.502, 'grad_norm': 0.24009312689304352, 'learning_rate': 2.2804799626870665e-06, 'epoch': 0.7784, 'num_input_tokens_seen': 4081057760, 'completed': '77.84% (973 / 1_250)', 'remaining time': '2:40:36', 'throughput': '117862.96', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:12:12,946 >> {'loss': 1.5895, 'grad_norm': 0.21253779530525208, 'learning_rate': 2.271712843165697e-06, 'epoch': 0.7792, 'num_input_tokens_seen': 4085252064, 'completed': '77.92% (974 / 1_250)', 'remaining time': '2:40:01', 'throughput': '118531.67', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:12:47,492 >> {'loss': 1.7404, 'grad_norm': 0.35227230191230774, 'learning_rate': 2.262970898476071e-06, 'epoch': 0.78, 'num_input_tokens_seen': 4089446368, 'completed': '78.00% (975 / 1_250)', 'remaining time': '2:39:27', 'throughput': '121411.76', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:13:23,014 >> {'loss': 1.7723, 'grad_norm': 0.23469075560569763, 'learning_rate': 2.2542541967896283e-06, 'epoch': 0.7808, 'num_input_tokens_seen': 4093640672, 'completed': '78.08% (976 / 1_250)', 'remaining time': '2:38:52', 'throughput': '118076.55', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:13:58,514 >> {'loss': 1.5612, 'grad_norm': 0.16704846918582916, 'learning_rate': 2.245562806080962e-06, 'epoch': 0.7816, 'num_input_tokens_seen': 4097834976, 'completed': '78.16% (977 / 1_250)', 'remaining time': '2:38:17', 'throughput': '118147.02', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:14:33,911 >> {'loss': 1.8197, 'grad_norm': 0.9915922284126282, 'learning_rate': 2.23689679412728e-06, 'epoch': 0.7824, 'num_input_tokens_seen': 4102029280, 'completed': '78.24% (978 / 1_250)', 'remaining time': '2:37:43', 'throughput': '118495.02', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:15:05,795 >> {'loss': 1.6457, 'grad_norm': 0.23591317236423492, 'learning_rate': 2.2282562285078877e-06, 'epoch': 0.7832, 'num_input_tokens_seen': 4106223584, 'completed': '78.32% (979 / 1_250)', 'remaining time': '2:37:07', 'throughput': '131550.38', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:15:40,300 >> {'loss': 1.4581, 'grad_norm': 0.17986330389976501, 'learning_rate': 2.2196411766036492e-06, 'epoch': 0.784, 'num_input_tokens_seen': 4110417888, 'completed': '78.40% (980 / 1_250)', 'remaining time': '2:36:32', 'throughput': '121556.02', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:16:15,133 >> {'loss': 1.5763, 'grad_norm': 0.28734660148620605, 'learning_rate': 2.2110517055964704e-06, 'epoch': 0.7848, 'num_input_tokens_seen': 4114612192, 'completed': '78.48% (981 / 1_250)', 'remaining time': '2:35:58', 'throughput': '120409.97', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:16:50,039 >> {'loss': 1.6441, 'grad_norm': 0.2190798819065094, 'learning_rate': 2.2024878824687704e-06, 'epoch': 0.7856, 'num_input_tokens_seen': 4118806496, 'completed': '78.56% (982 / 1_250)', 'remaining time': '2:35:23', 'throughput': '120160.32', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:17:25,493 >> {'loss': 1.5615, 'grad_norm': 0.18878762423992157, 'learning_rate': 2.1939497740029636e-06, 'epoch': 0.7864, 'num_input_tokens_seen': 4123000800, 'completed': '78.64% (983 / 1_250)', 'remaining time': '2:34:48', 'throughput': '118303.33', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:18:00,740 >> {'loss': 1.5576, 'grad_norm': 0.2658337950706482, 'learning_rate': 2.185437446780936e-06, 'epoch': 0.7872, 'num_input_tokens_seen': 4127195104, 'completed': '78.72% (984 / 1_250)', 'remaining time': '2:34:14', 'throughput': '118998.33', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:18:36,132 >> {'loss': 1.6773, 'grad_norm': 0.275441437959671, 'learning_rate': 2.1769509671835226e-06, 'epoch': 0.788, 'num_input_tokens_seen': 4131389408, 'completed': '78.80% (985 / 1_250)', 'remaining time': '2:33:39', 'throughput': '118510.22', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:19:10,769 >> {'loss': 1.6644, 'grad_norm': 0.18328648805618286, 'learning_rate': 2.168490401389999e-06, 'epoch': 0.7888, 'num_input_tokens_seen': 4135583712, 'completed': '78.88% (986 / 1_250)', 'remaining time': '2:33:04', 'throughput': '121093.18', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:19:46,243 >> {'loss': 1.4282, 'grad_norm': 0.14717541635036469, 'learning_rate': 2.1600558153775546e-06, 'epoch': 0.7896, 'num_input_tokens_seen': 4139778016, 'completed': '78.96% (987 / 1_250)', 'remaining time': '2:32:29', 'throughput': '118235.62', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:20:21,573 >> {'loss': 1.5961, 'grad_norm': 0.19601362943649292, 'learning_rate': 2.1516472749207867e-06, 'epoch': 0.7904, 'num_input_tokens_seen': 4143972320, 'completed': '79.04% (988 / 1_250)', 'remaining time': '2:31:55', 'throughput': '118716.35', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:20:56,676 >> {'loss': 1.6309, 'grad_norm': 0.19323942065238953, 'learning_rate': 2.143264845591181e-06, 'epoch': 0.7912, 'num_input_tokens_seen': 4148166624, 'completed': '79.12% (989 / 1_250)', 'remaining time': '2:31:20', 'throughput': '119485.10', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:21:31,339 >> {'loss': 1.7618, 'grad_norm': 0.38046109676361084, 'learning_rate': 2.1349085927566074e-06, 'epoch': 0.792, 'num_input_tokens_seen': 4152360928, 'completed': '79.20% (990 / 1_250)', 'remaining time': '2:30:45', 'throughput': '121003.25', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:22:06,699 >> {'loss': 1.758, 'grad_norm': 0.246466264128685, 'learning_rate': 2.1265785815808027e-06, 'epoch': 0.7928, 'num_input_tokens_seen': 4156555232, 'completed': '79.28% (991 / 1_250)', 'remaining time': '2:30:11', 'throughput': '118616.79', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:22:42,218 >> {'loss': 1.7367, 'grad_norm': 0.2647032141685486, 'learning_rate': 2.1182748770228686e-06, 'epoch': 0.7936, 'num_input_tokens_seen': 4160749536, 'completed': '79.36% (992 / 1_250)', 'remaining time': '2:29:36', 'throughput': '118087.87', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:23:17,519 >> {'loss': 1.6888, 'grad_norm': 0.4007807672023773, 'learning_rate': 2.1099975438367608e-06, 'epoch': 0.7944, 'num_input_tokens_seen': 4164943840, 'completed': '79.44% (993 / 1_250)', 'remaining time': '2:29:01', 'throughput': '118813.11', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:23:52,998 >> {'loss': 1.5346, 'grad_norm': 0.17826798558235168, 'learning_rate': 2.1017466465707843e-06, 'epoch': 0.7952, 'num_input_tokens_seen': 4169138144, 'completed': '79.52% (994 / 1_250)', 'remaining time': '2:28:27', 'throughput': '118220.47', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:24:27,928 >> {'loss': 1.6365, 'grad_norm': 0.19527707993984222, 'learning_rate': 2.093522249567097e-06, 'epoch': 0.796, 'num_input_tokens_seen': 4173332448, 'completed': '79.60% (995 / 1_250)', 'remaining time': '2:27:52', 'throughput': '120076.16', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:24:59,399 >> {'loss': 1.5653, 'grad_norm': 0.23201970756053925, 'learning_rate': 2.0853244169611954e-06, 'epoch': 0.7968, 'num_input_tokens_seen': 4177526752, 'completed': '79.68% (996 / 1_250)', 'remaining time': '2:27:16', 'throughput': '133275.27', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:25:31,483 >> {'loss': 1.7688, 'grad_norm': 0.20951257646083832, 'learning_rate': 2.077153212681428e-06, 'epoch': 0.7976, 'num_input_tokens_seen': 4181721056, 'completed': '79.76% (997 / 1_250)', 'remaining time': '2:26:41', 'throughput': '130730.67', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:26:06,709 >> {'loss': 1.6311, 'grad_norm': 0.1794024109840393, 'learning_rate': 2.0690087004484843e-06, 'epoch': 0.7984, 'num_input_tokens_seen': 4185915360, 'completed': '79.84% (998 / 1_250)', 'remaining time': '2:26:06', 'throughput': '119068.96', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:26:40,926 >> {'loss': 1.6188, 'grad_norm': 0.2026791125535965, 'learning_rate': 2.0608909437749097e-06, 'epoch': 0.7992, 'num_input_tokens_seen': 4190109664, 'completed': '79.92% (999 / 1_250)', 'remaining time': '2:25:31', 'throughput': '122578.31', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:27:16,220 >> {'loss': 1.7088, 'grad_norm': 0.26304003596305847, 'learning_rate': 2.0528000059646e-06, 'epoch': 0.8, 'num_input_tokens_seen': 4194303968, 'completed': '80.00% (1_000 / 1_250)', 'remaining time': '2:24:57', 'throughput': '118838.18', 'gpu_mem_free': '16314MB'} +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:689: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +[INFO|trainer.py:3503] 2026-05-02 11:27:25,241 >> Saving model checkpoint to /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-1000 +[INFO|configuration_utils.py:472] 2026-05-02 11:27:25,243 >> Configuration saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-1000/config.json +[INFO|configuration_utils.py:807] 2026-05-02 11:27:25,244 >> Configuration saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-1000/generation_config.json +[INFO|modeling_utils.py:2807] 2026-05-02 11:27:38,223 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 3 checkpoint shards. You can find where each parameters has been saved in the index located at /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-1000/model.safetensors.index.json. +[INFO|tokenization_utils_base.py:2684] 2026-05-02 11:27:38,225 >> tokenizer config file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-1000/tokenizer_config.json +[INFO|tokenization_utils_base.py:2693] 2026-05-02 11:27:38,225 >> Special tokens file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-1000/special_tokens_map.json +[INFO|tokenization_utils_base.py:2684] 2026-05-02 11:27:48,524 >> tokenizer config file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/tokenizer_config.json +[INFO|tokenization_utils_base.py:2693] 2026-05-02 11:27:48,524 >> Special tokens file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/special_tokens_map.json +[INFO|trainer.py:3595] 2026-05-02 11:27:48,544 >> Deleting older checkpoint [/tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-875] due to args.save_total_limit +[WARNING|trainer.py:870] 2026-05-02 11:27:49,704 >> Save streaming dataset state: {'epoch': 0, 'sample_in_epoch': 256000, 'num_canonical_nodes': 2, 'shuffle_seed': 42, 'initial_physical_nodes': 2} +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/utils/checkpoint.py:1399: FutureWarning: `torch.cpu.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cpu', args...)` instead. + with device_autocast_ctx, torch.cpu.amp.autocast(**cpu_autocast_kwargs), recompute_context: # type: ignore[attr-defined] +[INFO|trainer.py:175] 2026-05-02 11:28:25,206 >> {'loss': 1.5526, 'grad_norm': 0.20445233583450317, 'learning_rate': 2.0447359501123126e-06, 'epoch': 0.8008, 'num_input_tokens_seen': 4198498272, 'completed': '80.08% (1_001 / 1_250)', 'remaining time': '2:24:30', 'throughput': '60799.57', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:29:00,277 >> {'loss': 1.6392, 'grad_norm': 0.2073962539434433, 'learning_rate': 2.036698839103175e-06, 'epoch': 0.8016, 'num_input_tokens_seen': 4202692575, 'completed': '80.16% (1_002 / 1_250)', 'remaining time': '2:23:56', 'throughput': '119593.81', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:29:35,619 >> {'loss': 1.7117, 'grad_norm': 0.1796271651983261, 'learning_rate': 2.0286887356121944e-06, 'epoch': 0.8024, 'num_input_tokens_seen': 4206886879, 'completed': '80.24% (1_003 / 1_250)', 'remaining time': '2:23:21', 'throughput': '118677.40', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:30:10,969 >> {'loss': 1.7304, 'grad_norm': 0.1821316033601761, 'learning_rate': 2.020705702103767e-06, 'epoch': 0.8032, 'num_input_tokens_seen': 4211081183, 'completed': '80.32% (1_004 / 1_250)', 'remaining time': '2:22:46', 'throughput': '118653.36', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:30:42,750 >> {'loss': 1.5686, 'grad_norm': 0.24340355396270752, 'learning_rate': 2.0127498008311926e-06, 'epoch': 0.804, 'num_input_tokens_seen': 4215275487, 'completed': '80.40% (1_005 / 1_250)', 'remaining time': '2:22:11', 'throughput': '131973.87', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:31:17,171 >> {'loss': 1.5598, 'grad_norm': 0.17188352346420288, 'learning_rate': 2.0048210938361854e-06, 'epoch': 0.8048, 'num_input_tokens_seen': 4219469791, 'completed': '80.48% (1_006 / 1_250)', 'remaining time': '2:21:36', 'throughput': '121853.16', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:31:52,675 >> {'loss': 1.5954, 'grad_norm': 0.1990884393453598, 'learning_rate': 1.996919642948395e-06, 'epoch': 0.8056, 'num_input_tokens_seen': 4223664095, 'completed': '80.56% (1_007 / 1_250)', 'remaining time': '2:21:01', 'throughput': '118136.63', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:32:28,096 >> {'loss': 1.542, 'grad_norm': 0.20004838705062866, 'learning_rate': 1.9890455097849253e-06, 'epoch': 0.8064, 'num_input_tokens_seen': 4227858399, 'completed': '80.64% (1_008 / 1_250)', 'remaining time': '2:20:26', 'throughput': '118413.40', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:33:03,521 >> {'loss': 1.8303, 'grad_norm': 0.23419179022312164, 'learning_rate': 1.9811987557498452e-06, 'epoch': 0.8072, 'num_input_tokens_seen': 4232052703, 'completed': '80.72% (1_009 / 1_250)', 'remaining time': '2:19:52', 'throughput': '118397.56', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:33:38,794 >> {'loss': 1.7563, 'grad_norm': 0.2528334856033325, 'learning_rate': 1.9733794420337214e-06, 'epoch': 0.808, 'num_input_tokens_seen': 4236247007, 'completed': '80.80% (1_010 / 1_250)', 'remaining time': '2:19:17', 'throughput': '118911.21', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:34:14,034 >> {'loss': 1.6681, 'grad_norm': 0.1960066705942154, 'learning_rate': 1.9655876296131318e-06, 'epoch': 0.8088, 'num_input_tokens_seen': 4240441311, 'completed': '80.88% (1_011 / 1_250)', 'remaining time': '2:18:42', 'throughput': '119019.79', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:34:49,591 >> {'loss': 1.5386, 'grad_norm': 0.36464717984199524, 'learning_rate': 1.9578233792501957e-06, 'epoch': 0.8096, 'num_input_tokens_seen': 4244635615, 'completed': '80.96% (1_012 / 1_250)', 'remaining time': '2:18:08', 'throughput': '117959.79', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:35:20,668 >> {'loss': 1.5592, 'grad_norm': 0.18706953525543213, 'learning_rate': 1.9500867514920974e-06, 'epoch': 0.8104, 'num_input_tokens_seen': 4248829919, 'completed': '81.04% (1_013 / 1_250)', 'remaining time': '2:17:32', 'throughput': '134964.69', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:35:54,469 >> {'loss': 1.67, 'grad_norm': 0.22275422513484955, 'learning_rate': 1.9423778066706116e-06, 'epoch': 0.8112, 'num_input_tokens_seen': 4253024223, 'completed': '81.12% (1_014 / 1_250)', 'remaining time': '2:16:57', 'throughput': '124088.96', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:36:29,902 >> {'loss': 1.6496, 'grad_norm': 0.16965825855731964, 'learning_rate': 1.9346966049016423e-06, 'epoch': 0.812, 'num_input_tokens_seen': 4257218527, 'completed': '81.20% (1_015 / 1_250)', 'remaining time': '2:16:22', 'throughput': '118372.41', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:37:05,430 >> {'loss': 1.6489, 'grad_norm': 0.19543571770191193, 'learning_rate': 1.927043206084741e-06, 'epoch': 0.8128, 'num_input_tokens_seen': 4261412831, 'completed': '81.28% (1_016 / 1_250)', 'remaining time': '2:15:47', 'throughput': '118058.00', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:37:40,809 >> {'loss': 1.6654, 'grad_norm': 0.22528451681137085, 'learning_rate': 1.9194176699026506e-06, 'epoch': 0.8136, 'num_input_tokens_seen': 4265607135, 'completed': '81.36% (1_017 / 1_250)', 'remaining time': '2:15:13', 'throughput': '118553.57', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:38:16,189 >> {'loss': 1.541, 'grad_norm': 0.15479516983032227, 'learning_rate': 1.9118200558208343e-06, 'epoch': 0.8144, 'num_input_tokens_seen': 4269801439, 'completed': '81.44% (1_018 / 1_250)', 'remaining time': '2:14:38', 'throughput': '118547.52', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:38:51,588 >> {'loss': 1.7252, 'grad_norm': 0.21417930722236633, 'learning_rate': 1.9042504230870123e-06, 'epoch': 0.8152, 'num_input_tokens_seen': 4273995743, 'completed': '81.52% (1_019 / 1_250)', 'remaining time': '2:14:03', 'throughput': '118488.43', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:39:26,931 >> {'loss': 1.6182, 'grad_norm': 0.20388461649417877, 'learning_rate': 1.8967088307307002e-06, 'epoch': 0.816, 'num_input_tokens_seen': 4278190047, 'completed': '81.60% (1_020 / 1_250)', 'remaining time': '2:13:29', 'throughput': '118673.87', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:40:02,143 >> {'loss': 1.6578, 'grad_norm': 0.16141732037067413, 'learning_rate': 1.8891953375627515e-06, 'epoch': 0.8168, 'num_input_tokens_seen': 4282384351, 'completed': '81.68% (1_021 / 1_250)', 'remaining time': '2:12:54', 'throughput': '119114.08', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:40:37,600 >> {'loss': 1.5268, 'grad_norm': 0.23652295768260956, 'learning_rate': 1.8817100021748943e-06, 'epoch': 0.8176, 'num_input_tokens_seen': 4286578655, 'completed': '81.76% (1_022 / 1_250)', 'remaining time': '2:12:19', 'throughput': '118295.46', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:41:09,078 >> {'loss': 1.7283, 'grad_norm': 0.19557224214076996, 'learning_rate': 1.8742528829392782e-06, 'epoch': 0.8184, 'num_input_tokens_seen': 4290772959, 'completed': '81.84% (1_023 / 1_250)', 'remaining time': '2:11:44', 'throughput': '133242.00', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:41:41,149 >> {'loss': 1.4667, 'grad_norm': 0.23148322105407715, 'learning_rate': 1.8668240380080174e-06, 'epoch': 0.8192, 'num_input_tokens_seen': 4294967263, 'completed': '81.92% (1_024 / 1_250)', 'remaining time': '2:11:08', 'throughput': '130783.57', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:42:16,456 >> {'loss': 1.7139, 'grad_norm': 0.17833733558654785, 'learning_rate': 1.8594235253127373e-06, 'epoch': 0.82, 'num_input_tokens_seen': 4299161567, 'completed': '82.00% (1_025 / 1_250)', 'remaining time': '2:10:34', 'throughput': '118796.51', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:42:50,440 >> {'loss': 1.5541, 'grad_norm': 0.2520832419395447, 'learning_rate': 1.852051402564121e-06, 'epoch': 0.8208, 'num_input_tokens_seen': 4303355871, 'completed': '82.08% (1_026 / 1_250)', 'remaining time': '2:09:59', 'throughput': '123417.08', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:43:26,117 >> {'loss': 1.5341, 'grad_norm': 0.2509540915489197, 'learning_rate': 1.8447077272514628e-06, 'epoch': 0.8216, 'num_input_tokens_seen': 4307550174, 'completed': '82.16% (1_027 / 1_250)', 'remaining time': '2:09:24', 'throughput': '117563.78', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:44:00,139 >> {'loss': 1.6876, 'grad_norm': 0.22817407548427582, 'learning_rate': 1.8373925566422196e-06, 'epoch': 0.8224, 'num_input_tokens_seen': 4311744478, 'completed': '82.24% (1_028 / 1_250)', 'remaining time': '2:08:49', 'throughput': '123282.84', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:44:35,291 >> {'loss': 1.6795, 'grad_norm': 0.22014537453651428, 'learning_rate': 1.8301059477815585e-06, 'epoch': 0.8232, 'num_input_tokens_seen': 4315938782, 'completed': '82.32% (1_029 / 1_250)', 'remaining time': '2:08:14', 'throughput': '119320.10', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:45:10,661 >> {'loss': 1.8483, 'grad_norm': 0.24150323867797852, 'learning_rate': 1.8228479574919222e-06, 'epoch': 0.824, 'num_input_tokens_seen': 4320133086, 'completed': '82.40% (1_030 / 1_250)', 'remaining time': '2:07:40', 'throughput': '118583.41', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:45:46,127 >> {'loss': 1.448, 'grad_norm': 0.21320360898971558, 'learning_rate': 1.8156186423725752e-06, 'epoch': 0.8248, 'num_input_tokens_seen': 4324327390, 'completed': '82.48% (1_031 / 1_250)', 'remaining time': '2:07:05', 'throughput': '118263.50', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:46:17,543 >> {'loss': 1.6404, 'grad_norm': 0.21376678347587585, 'learning_rate': 1.80841805879917e-06, 'epoch': 0.8256, 'num_input_tokens_seen': 4328521694, 'completed': '82.56% (1_032 / 1_250)', 'remaining time': '2:06:29', 'throughput': '133504.58', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:46:48,564 >> {'loss': 1.5614, 'grad_norm': 0.24570904672145844, 'learning_rate': 1.8012462629233014e-06, 'epoch': 0.8264, 'num_input_tokens_seen': 4332715998, 'completed': '82.64% (1_033 / 1_250)', 'remaining time': '2:05:54', 'throughput': '135208.61', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:47:23,985 >> {'loss': 1.4638, 'grad_norm': 0.15780524909496307, 'learning_rate': 1.7941033106720769e-06, 'epoch': 0.8272, 'num_input_tokens_seen': 4336910302, 'completed': '82.72% (1_034 / 1_250)', 'remaining time': '2:05:19', 'throughput': '118414.52', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:47:58,484 >> {'loss': 1.6656, 'grad_norm': 0.21874788403511047, 'learning_rate': 1.7869892577476725e-06, 'epoch': 0.828, 'num_input_tokens_seen': 4341104606, 'completed': '82.80% (1_035 / 1_250)', 'remaining time': '2:04:44', 'throughput': '121576.68', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:48:33,921 >> {'loss': 1.573, 'grad_norm': 0.16850021481513977, 'learning_rate': 1.7799041596269006e-06, 'epoch': 0.8288, 'num_input_tokens_seen': 4345298910, 'completed': '82.88% (1_036 / 1_250)', 'remaining time': '2:04:09', 'throughput': '118359.06', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:49:04,707 >> {'loss': 1.5421, 'grad_norm': 0.2278273105621338, 'learning_rate': 1.7728480715607815e-06, 'epoch': 0.8296, 'num_input_tokens_seen': 4349493214, 'completed': '82.96% (1_037 / 1_250)', 'remaining time': '2:03:34', 'throughput': '136241.31', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:49:39,634 >> {'loss': 1.5368, 'grad_norm': 0.19504031538963318, 'learning_rate': 1.7658210485741067e-06, 'epoch': 0.8304, 'num_input_tokens_seen': 4353687518, 'completed': '83.04% (1_038 / 1_250)', 'remaining time': '2:02:59', 'throughput': '120089.41', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:50:14,760 >> {'loss': 1.8269, 'grad_norm': 0.19000563025474548, 'learning_rate': 1.7588231454650128e-06, 'epoch': 0.8312, 'num_input_tokens_seen': 4357881822, 'completed': '83.12% (1_039 / 1_250)', 'remaining time': '2:02:24', 'throughput': '119407.15', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:50:50,106 >> {'loss': 1.5509, 'grad_norm': 0.17575758695602417, 'learning_rate': 1.7518544168045527e-06, 'epoch': 0.832, 'num_input_tokens_seen': 4362076126, 'completed': '83.20% (1_040 / 1_250)', 'remaining time': '2:01:50', 'throughput': '118664.00', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:51:25,513 >> {'loss': 1.6646, 'grad_norm': 0.2147795706987381, 'learning_rate': 1.744914916936275e-06, 'epoch': 0.8328, 'num_input_tokens_seen': 4366270429, 'completed': '83.28% (1_041 / 1_250)', 'remaining time': '2:01:15', 'throughput': '118460.78', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:52:00,780 >> {'loss': 1.6989, 'grad_norm': 0.2155894935131073, 'learning_rate': 1.738004699975791e-06, 'epoch': 0.8336, 'num_input_tokens_seen': 4370464733, 'completed': '83.36% (1_042 / 1_250)', 'remaining time': '2:00:40', 'throughput': '118928.85', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:52:36,162 >> {'loss': 1.5607, 'grad_norm': 0.16649827361106873, 'learning_rate': 1.7311238198103627e-06, 'epoch': 0.8344, 'num_input_tokens_seen': 4374659037, 'completed': '83.44% (1_043 / 1_250)', 'remaining time': '2:00:05', 'throughput': '118544.44', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:53:11,232 >> {'loss': 1.6791, 'grad_norm': 0.20195800065994263, 'learning_rate': 1.7242723300984754e-06, 'epoch': 0.8352, 'num_input_tokens_seen': 4378853341, 'completed': '83.52% (1_044 / 1_250)', 'remaining time': '1:59:31', 'throughput': '119597.70', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:53:46,197 >> {'loss': 1.4888, 'grad_norm': 0.16663207113742828, 'learning_rate': 1.7174502842694212e-06, 'epoch': 0.836, 'num_input_tokens_seen': 4383047645, 'completed': '83.60% (1_045 / 1_250)', 'remaining time': '1:58:56', 'throughput': '119956.31', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:54:21,582 >> {'loss': 1.521, 'grad_norm': 0.20622679591178894, 'learning_rate': 1.7106577355228854e-06, 'epoch': 0.8368, 'num_input_tokens_seen': 4387241949, 'completed': '83.68% (1_046 / 1_250)', 'remaining time': '1:58:21', 'throughput': '118533.33', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:54:55,503 >> {'loss': 1.6856, 'grad_norm': 0.18426112830638885, 'learning_rate': 1.7038947368285258e-06, 'epoch': 0.8376, 'num_input_tokens_seen': 4391436253, 'completed': '83.76% (1_047 / 1_250)', 'remaining time': '1:57:46', 'throughput': '123650.45', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:55:30,962 >> {'loss': 1.4483, 'grad_norm': 0.23764491081237793, 'learning_rate': 1.6971613409255666e-06, 'epoch': 0.8384, 'num_input_tokens_seen': 4395630557, 'completed': '83.84% (1_048 / 1_250)', 'remaining time': '1:57:12', 'throughput': '118283.80', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:56:05,367 >> {'loss': 1.6326, 'grad_norm': 0.1989714652299881, 'learning_rate': 1.6904576003223794e-06, 'epoch': 0.8392, 'num_input_tokens_seen': 4399824860, 'completed': '83.92% (1_049 / 1_250)', 'remaining time': '1:56:37', 'throughput': '121909.68', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:56:39,196 >> {'loss': 1.5191, 'grad_norm': 0.168902188539505, 'learning_rate': 1.6837835672960834e-06, 'epoch': 0.84, 'num_input_tokens_seen': 4404019164, 'completed': '84.00% (1_050 / 1_250)', 'remaining time': '1:56:02', 'throughput': '123986.24', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:57:14,316 >> {'loss': 1.5835, 'grad_norm': 0.22392895817756653, 'learning_rate': 1.6771392938921266e-06, 'epoch': 0.8408, 'num_input_tokens_seen': 4408213468, 'completed': '84.08% (1_051 / 1_250)', 'remaining time': '1:55:27', 'throughput': '119429.05', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:57:48,266 >> {'loss': 1.3059, 'grad_norm': 0.18032029271125793, 'learning_rate': 1.6705248319238875e-06, 'epoch': 0.8416, 'num_input_tokens_seen': 4412407772, 'completed': '84.16% (1_052 / 1_250)', 'remaining time': '1:54:52', 'throughput': '123543.49', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:58:23,680 >> {'loss': 1.6117, 'grad_norm': 0.19046376645565033, 'learning_rate': 1.6639402329722692e-06, 'epoch': 0.8424, 'num_input_tokens_seen': 4416602076, 'completed': '84.24% (1_053 / 1_250)', 'remaining time': '1:54:17', 'throughput': '118436.60', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:58:57,846 >> {'loss': 1.6446, 'grad_norm': 0.2442684769630432, 'learning_rate': 1.6573855483852974e-06, 'epoch': 0.8432, 'num_input_tokens_seen': 4420796380, 'completed': '84.32% (1_054 / 1_250)', 'remaining time': '1:53:42', 'throughput': '122762.49', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 11:59:33,232 >> {'loss': 1.3933, 'grad_norm': 0.19598646461963654, 'learning_rate': 1.6508608292777205e-06, 'epoch': 0.844, 'num_input_tokens_seen': 4424990684, 'completed': '84.40% (1_055 / 1_250)', 'remaining time': '1:53:08', 'throughput': '118530.21', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:00:08,702 >> {'loss': 1.6186, 'grad_norm': 0.17496395111083984, 'learning_rate': 1.644366126530607e-06, 'epoch': 0.8448, 'num_input_tokens_seen': 4429184988, 'completed': '84.48% (1_056 / 1_250)', 'remaining time': '1:52:33', 'throughput': '118247.99', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:00:44,079 >> {'loss': 1.7042, 'grad_norm': 0.17825818061828613, 'learning_rate': 1.6379014907909553e-06, 'epoch': 0.8456, 'num_input_tokens_seen': 4433379292, 'completed': '84.56% (1_057 / 1_250)', 'remaining time': '1:51:58', 'throughput': '118559.10', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:01:19,434 >> {'loss': 1.5923, 'grad_norm': 0.2415654957294464, 'learning_rate': 1.6314669724712906e-06, 'epoch': 0.8464, 'num_input_tokens_seen': 4437573595, 'completed': '84.64% (1_058 / 1_250)', 'remaining time': '1:51:24', 'throughput': '118634.11', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:01:54,750 >> {'loss': 1.7453, 'grad_norm': 0.1992741823196411, 'learning_rate': 1.6250626217492821e-06, 'epoch': 0.8472, 'num_input_tokens_seen': 4441767899, 'completed': '84.72% (1_059 / 1_250)', 'remaining time': '1:50:49', 'throughput': '118767.28', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:02:30,215 >> {'loss': 1.6084, 'grad_norm': 0.20831193029880524, 'learning_rate': 1.6186884885673414e-06, 'epoch': 0.848, 'num_input_tokens_seen': 4445962203, 'completed': '84.80% (1_060 / 1_250)', 'remaining time': '1:50:14', 'throughput': '118263.66', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:03:05,408 >> {'loss': 1.5342, 'grad_norm': 0.19565336406230927, 'learning_rate': 1.6123446226322414e-06, 'epoch': 0.8488, 'num_input_tokens_seen': 4450156507, 'completed': '84.88% (1_061 / 1_250)', 'remaining time': '1:49:39', 'throughput': '119180.85', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:03:40,193 >> {'loss': 1.593, 'grad_norm': 0.16339339315891266, 'learning_rate': 1.606031073414721e-06, 'epoch': 0.8496, 'num_input_tokens_seen': 4454350811, 'completed': '84.96% (1_062 / 1_250)', 'remaining time': '1:49:05', 'throughput': '120576.48', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:04:15,291 >> {'loss': 1.5973, 'grad_norm': 0.25184905529022217, 'learning_rate': 1.5997478901491076e-06, 'epoch': 0.8504, 'num_input_tokens_seen': 4458545115, 'completed': '85.04% (1_063 / 1_250)', 'remaining time': '1:48:30', 'throughput': '119502.74', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:04:47,038 >> {'loss': 1.7505, 'grad_norm': 0.18604181706905365, 'learning_rate': 1.5934951218329242e-06, 'epoch': 0.8512, 'num_input_tokens_seen': 4462739419, 'completed': '85.12% (1_064 / 1_250)', 'remaining time': '1:47:54', 'throughput': '132118.57', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:05:22,118 >> {'loss': 1.7674, 'grad_norm': 0.19056926667690277, 'learning_rate': 1.5872728172265148e-06, 'epoch': 0.852, 'num_input_tokens_seen': 4466933723, 'completed': '85.20% (1_065 / 1_250)', 'remaining time': '1:47:20', 'throughput': '119563.44', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:05:56,262 >> {'loss': 1.6087, 'grad_norm': 0.19127880036830902, 'learning_rate': 1.5810810248526612e-06, 'epoch': 0.8528, 'num_input_tokens_seen': 4471128027, 'completed': '85.28% (1_066 / 1_250)', 'remaining time': '1:46:45', 'throughput': '122843.32', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:06:31,871 >> {'loss': 1.519, 'grad_norm': 0.1688477098941803, 'learning_rate': 1.5749197929962035e-06, 'epoch': 0.8536, 'num_input_tokens_seen': 4475322331, 'completed': '85.36% (1_067 / 1_250)', 'remaining time': '1:46:10', 'throughput': '117785.44', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:07:07,082 >> {'loss': 1.7403, 'grad_norm': 0.18508239090442657, 'learning_rate': 1.5687891697036662e-06, 'epoch': 0.8544, 'num_input_tokens_seen': 4479516635, 'completed': '85.44% (1_068 / 1_250)', 'remaining time': '1:45:35', 'throughput': '119120.74', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:07:42,613 >> {'loss': 1.4453, 'grad_norm': 0.17140759527683258, 'learning_rate': 1.562689202782881e-06, 'epoch': 0.8552, 'num_input_tokens_seen': 4483710939, 'completed': '85.52% (1_069 / 1_250)', 'remaining time': '1:45:01', 'throughput': '118044.28', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:08:17,853 >> {'loss': 1.6433, 'grad_norm': 0.1710292249917984, 'learning_rate': 1.556619939802615e-06, 'epoch': 0.856, 'num_input_tokens_seen': 4487905243, 'completed': '85.60% (1_070 / 1_250)', 'remaining time': '1:44:26', 'throughput': '119021.74', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:08:53,061 >> {'loss': 1.5979, 'grad_norm': 0.20817092061042786, 'learning_rate': 1.5505814280921991e-06, 'epoch': 0.8568, 'num_input_tokens_seen': 4492099547, 'completed': '85.68% (1_071 / 1_250)', 'remaining time': '1:43:51', 'throughput': '119129.37', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:09:28,357 >> {'loss': 1.7456, 'grad_norm': 0.18353237211704254, 'learning_rate': 1.5445737147411627e-06, 'epoch': 0.8576, 'num_input_tokens_seen': 4496293851, 'completed': '85.76% (1_072 / 1_250)', 'remaining time': '1:43:16', 'throughput': '118832.05', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:10:03,853 >> {'loss': 1.6733, 'grad_norm': 0.22432063519954681, 'learning_rate': 1.5385968465988592e-06, 'epoch': 0.8584, 'num_input_tokens_seen': 4500488155, 'completed': '85.84% (1_073 / 1_250)', 'remaining time': '1:42:42', 'throughput': '118164.14', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:10:39,074 >> {'loss': 1.5844, 'grad_norm': 0.180768221616745, 'learning_rate': 1.5326508702741094e-06, 'epoch': 0.8592, 'num_input_tokens_seen': 4504682459, 'completed': '85.92% (1_074 / 1_250)', 'remaining time': '1:42:07', 'throughput': '119084.22', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:11:14,505 >> {'loss': 1.565, 'grad_norm': 0.1490861177444458, 'learning_rate': 1.526735832134829e-06, 'epoch': 0.86, 'num_input_tokens_seen': 4508876763, 'completed': '86.00% (1_075 / 1_250)', 'remaining time': '1:41:32', 'throughput': '118379.21', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:11:49,963 >> {'loss': 1.6147, 'grad_norm': 0.18960492312908173, 'learning_rate': 1.5208517783076749e-06, 'epoch': 0.8608, 'num_input_tokens_seen': 4513071067, 'completed': '86.08% (1_076 / 1_250)', 'remaining time': '1:40:58', 'throughput': '118291.63', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:12:20,831 >> {'loss': 1.6762, 'grad_norm': 0.25294896960258484, 'learning_rate': 1.5149987546776806e-06, 'epoch': 0.8616, 'num_input_tokens_seen': 4517265371, 'completed': '86.16% (1_077 / 1_250)', 'remaining time': '1:40:22', 'throughput': '135877.06', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:12:56,270 >> {'loss': 1.7769, 'grad_norm': 0.1851082295179367, 'learning_rate': 1.509176806887899e-06, 'epoch': 0.8624, 'num_input_tokens_seen': 4521459675, 'completed': '86.24% (1_078 / 1_250)', 'remaining time': '1:39:47', 'throughput': '118351.48', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:13:30,942 >> {'loss': 1.497, 'grad_norm': 0.2860797345638275, 'learning_rate': 1.50338598033905e-06, 'epoch': 0.8632, 'num_input_tokens_seen': 4525653979, 'completed': '86.32% (1_079 / 1_250)', 'remaining time': '1:39:13', 'throughput': '120972.17', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:14:05,477 >> {'loss': 1.5841, 'grad_norm': 0.18727374076843262, 'learning_rate': 1.4976263201891613e-06, 'epoch': 0.864, 'num_input_tokens_seen': 4529848283, 'completed': '86.40% (1_080 / 1_250)', 'remaining time': '1:38:38', 'throughput': '121451.83', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:14:40,969 >> {'loss': 1.7158, 'grad_norm': 0.1551392674446106, 'learning_rate': 1.4918978713532206e-06, 'epoch': 0.8648, 'num_input_tokens_seen': 4534042587, 'completed': '86.48% (1_081 / 1_250)', 'remaining time': '1:38:03', 'throughput': '118175.13', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:15:15,153 >> {'loss': 1.6347, 'grad_norm': 0.2355329841375351, 'learning_rate': 1.4862006785028218e-06, 'epoch': 0.8656, 'num_input_tokens_seen': 4538236891, 'completed': '86.56% (1_082 / 1_250)', 'remaining time': '1:37:28', 'throughput': '122698.35', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:15:50,563 >> {'loss': 1.8263, 'grad_norm': 0.22274082899093628, 'learning_rate': 1.4805347860658198e-06, 'epoch': 0.8664, 'num_input_tokens_seen': 4542431195, 'completed': '86.64% (1_083 / 1_250)', 'remaining time': '1:36:53', 'throughput': '118449.18', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:16:25,897 >> {'loss': 1.7084, 'grad_norm': 0.1815938949584961, 'learning_rate': 1.4749002382259815e-06, 'epoch': 0.8672, 'num_input_tokens_seen': 4546625499, 'completed': '86.72% (1_084 / 1_250)', 'remaining time': '1:36:19', 'throughput': '118703.08', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:17:01,217 >> {'loss': 1.5642, 'grad_norm': 0.22860968112945557, 'learning_rate': 1.4692970789226421e-06, 'epoch': 0.868, 'num_input_tokens_seen': 4550819803, 'completed': '86.80% (1_085 / 1_250)', 'remaining time': '1:35:44', 'throughput': '118752.03', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:17:36,689 >> {'loss': 1.7357, 'grad_norm': 0.18680602312088013, 'learning_rate': 1.4637253518503656e-06, 'epoch': 0.8688, 'num_input_tokens_seen': 4555014107, 'completed': '86.88% (1_086 / 1_250)', 'remaining time': '1:35:09', 'throughput': '118243.44', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:18:07,986 >> {'loss': 1.7161, 'grad_norm': 0.23066458106040955, 'learning_rate': 1.4581851004585968e-06, 'epoch': 0.8696, 'num_input_tokens_seen': 4559208411, 'completed': '86.96% (1_087 / 1_250)', 'remaining time': '1:34:34', 'throughput': '134015.93', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:18:43,098 >> {'loss': 1.7565, 'grad_norm': 0.25282004475593567, 'learning_rate': 1.4526763679513302e-06, 'epoch': 0.8704, 'num_input_tokens_seen': 4563402715, 'completed': '87.04% (1_088 / 1_250)', 'remaining time': '1:33:59', 'throughput': '119455.62', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:19:18,236 >> {'loss': 1.6771, 'grad_norm': 0.22142787277698517, 'learning_rate': 1.4471991972867688e-06, 'epoch': 0.8712, 'num_input_tokens_seen': 4567597019, 'completed': '87.12% (1_089 / 1_250)', 'remaining time': '1:33:24', 'throughput': '119368.03', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:19:53,499 >> {'loss': 1.7245, 'grad_norm': 0.21299467980861664, 'learning_rate': 1.4417536311769885e-06, 'epoch': 0.872, 'num_input_tokens_seen': 4571791323, 'completed': '87.20% (1_090 / 1_250)', 'remaining time': '1:32:50', 'throughput': '118942.89', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:20:28,760 >> {'loss': 1.6207, 'grad_norm': 0.21825799345970154, 'learning_rate': 1.4363397120876082e-06, 'epoch': 0.8728, 'num_input_tokens_seen': 4575985627, 'completed': '87.28% (1_091 / 1_250)', 'remaining time': '1:32:15', 'throughput': '118949.31', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:21:03,046 >> {'loss': 1.5993, 'grad_norm': 0.1794862598180771, 'learning_rate': 1.4309574822374564e-06, 'epoch': 0.8736, 'num_input_tokens_seen': 4580179931, 'completed': '87.36% (1_092 / 1_250)', 'remaining time': '1:31:40', 'throughput': '122333.12', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:21:37,248 >> {'loss': 1.3508, 'grad_norm': 0.16706892848014832, 'learning_rate': 1.4256069835982422e-06, 'epoch': 0.8744, 'num_input_tokens_seen': 4584374235, 'completed': '87.44% (1_093 / 1_250)', 'remaining time': '1:31:05', 'throughput': '122632.47', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:22:12,384 >> {'loss': 1.3738, 'grad_norm': 0.17619284987449646, 'learning_rate': 1.4202882578942307e-06, 'epoch': 0.8752, 'num_input_tokens_seen': 4588568539, 'completed': '87.52% (1_094 / 1_250)', 'remaining time': '1:30:30', 'throughput': '119375.15', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:22:47,337 >> {'loss': 1.5672, 'grad_norm': 0.18327082693576813, 'learning_rate': 1.4150013466019116e-06, 'epoch': 0.876, 'num_input_tokens_seen': 4592762843, 'completed': '87.60% (1_095 / 1_250)', 'remaining time': '1:29:55', 'throughput': '119997.94', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:23:22,707 >> {'loss': 1.4859, 'grad_norm': 0.2004118710756302, 'learning_rate': 1.4097462909496809e-06, 'epoch': 0.8768, 'num_input_tokens_seen': 4596957146, 'completed': '87.68% (1_096 / 1_250)', 'remaining time': '1:29:21', 'throughput': '118583.05', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:23:58,083 >> {'loss': 1.8443, 'grad_norm': 0.19041939079761505, 'learning_rate': 1.4045231319175199e-06, 'epoch': 0.8776, 'num_input_tokens_seen': 4601151450, 'completed': '87.76% (1_097 / 1_250)', 'remaining time': '1:28:46', 'throughput': '118563.30', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:24:33,574 >> {'loss': 1.6275, 'grad_norm': 0.3050411343574524, 'learning_rate': 1.3993319102366703e-06, 'epoch': 0.8784, 'num_input_tokens_seen': 4605345754, 'completed': '87.84% (1_098 / 1_250)', 'remaining time': '1:28:11', 'throughput': '118178.47', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:25:08,081 >> {'loss': 1.6106, 'grad_norm': 0.1771000623703003, 'learning_rate': 1.394172666389323e-06, 'epoch': 0.8792, 'num_input_tokens_seen': 4609540058, 'completed': '87.92% (1_099 / 1_250)', 'remaining time': '1:27:36', 'throughput': '121550.81', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:25:43,291 >> {'loss': 1.56, 'grad_norm': 0.20475603640079498, 'learning_rate': 1.389045440608296e-06, 'epoch': 0.88, 'num_input_tokens_seen': 4613734362, 'completed': '88.00% (1_100 / 1_250)', 'remaining time': '1:27:02', 'throughput': '119121.00', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:26:17,290 >> {'loss': 1.6032, 'grad_norm': 0.17201325297355652, 'learning_rate': 1.3839502728767278e-06, 'epoch': 0.8808, 'num_input_tokens_seen': 4617928666, 'completed': '88.08% (1_101 / 1_250)', 'remaining time': '1:26:27', 'throughput': '123368.31', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:26:51,856 >> {'loss': 1.6242, 'grad_norm': 0.2655251622200012, 'learning_rate': 1.3788872029277594e-06, 'epoch': 0.8816, 'num_input_tokens_seen': 4622122970, 'completed': '88.16% (1_102 / 1_250)', 'remaining time': '1:25:52', 'throughput': '121340.96', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:27:27,283 >> {'loss': 1.5282, 'grad_norm': 0.15565548837184906, 'learning_rate': 1.373856270244227e-06, 'epoch': 0.8824, 'num_input_tokens_seen': 4626317273, 'completed': '88.24% (1_103 / 1_250)', 'remaining time': '1:25:17', 'throughput': '118390.84', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:28:02,716 >> {'loss': 1.7713, 'grad_norm': 0.19305945932865143, 'learning_rate': 1.3688575140583536e-06, 'epoch': 0.8832, 'num_input_tokens_seen': 4630511577, 'completed': '88.32% (1_104 / 1_250)', 'remaining time': '1:24:42', 'throughput': '118375.17', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:28:38,252 >> {'loss': 1.6871, 'grad_norm': 0.16828465461730957, 'learning_rate': 1.3638909733514456e-06, 'epoch': 0.884, 'num_input_tokens_seen': 4634705881, 'completed': '88.40% (1_105 / 1_250)', 'remaining time': '1:24:08', 'throughput': '118027.97', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:29:13,535 >> {'loss': 1.6235, 'grad_norm': 0.21523800492286682, 'learning_rate': 1.3589566868535835e-06, 'epoch': 0.8848, 'num_input_tokens_seen': 4638900185, 'completed': '88.48% (1_106 / 1_250)', 'remaining time': '1:23:33', 'throughput': '118876.16', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:29:48,931 >> {'loss': 1.4298, 'grad_norm': 0.17122241854667664, 'learning_rate': 1.3540546930433265e-06, 'epoch': 0.8856, 'num_input_tokens_seen': 4643094489, 'completed': '88.56% (1_107 / 1_250)', 'remaining time': '1:22:58', 'throughput': '118498.59', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:30:24,043 >> {'loss': 1.623, 'grad_norm': 0.1741933375597, 'learning_rate': 1.3491850301474058e-06, 'epoch': 0.8864, 'num_input_tokens_seen': 4647288793, 'completed': '88.64% (1_108 / 1_250)', 'remaining time': '1:22:23', 'throughput': '119452.40', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:30:59,592 >> {'loss': 1.6175, 'grad_norm': 0.22509343922138214, 'learning_rate': 1.34434773614043e-06, 'epoch': 0.8872, 'num_input_tokens_seen': 4651483097, 'completed': '88.72% (1_109 / 1_250)', 'remaining time': '1:21:49', 'throughput': '117988.37', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:31:34,299 >> {'loss': 1.5291, 'grad_norm': 0.20347225666046143, 'learning_rate': 1.3395428487445916e-06, 'epoch': 0.888, 'num_input_tokens_seen': 4655677401, 'completed': '88.80% (1_110 / 1_250)', 'remaining time': '1:21:14', 'throughput': '120848.22', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:32:08,629 >> {'loss': 1.6873, 'grad_norm': 0.1749250590801239, 'learning_rate': 1.3347704054293657e-06, 'epoch': 0.8888, 'num_input_tokens_seen': 4659871705, 'completed': '88.88% (1_111 / 1_250)', 'remaining time': '1:20:39', 'throughput': '122175.68', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:32:44,010 >> {'loss': 1.561, 'grad_norm': 0.21389378607273102, 'learning_rate': 1.3300304434112258e-06, 'epoch': 0.8896, 'num_input_tokens_seen': 4664066009, 'completed': '88.96% (1_112 / 1_250)', 'remaining time': '1:20:04', 'throughput': '118548.69', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:33:14,730 >> {'loss': 1.7735, 'grad_norm': 0.20146727561950684, 'learning_rate': 1.3253229996533459e-06, 'epoch': 0.8904, 'num_input_tokens_seen': 4668260313, 'completed': '89.04% (1_113 / 1_250)', 'remaining time': '1:19:29', 'throughput': '136532.18', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:33:48,980 >> {'loss': 1.5615, 'grad_norm': 0.1519114226102829, 'learning_rate': 1.3206481108653207e-06, 'epoch': 0.8912, 'num_input_tokens_seen': 4672454617, 'completed': '89.12% (1_114 / 1_250)', 'remaining time': '1:18:54', 'throughput': '122461.46', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:34:24,215 >> {'loss': 1.4648, 'grad_norm': 0.16608597338199615, 'learning_rate': 1.316005813502869e-06, 'epoch': 0.892, 'num_input_tokens_seen': 4676648921, 'completed': '89.20% (1_115 / 1_250)', 'remaining time': '1:18:19', 'throughput': '119037.67', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:34:59,523 >> {'loss': 1.6871, 'grad_norm': 0.22237703204154968, 'learning_rate': 1.3113961437675598e-06, 'epoch': 0.8928, 'num_input_tokens_seen': 4680843225, 'completed': '89.28% (1_116 / 1_250)', 'remaining time': '1:17:44', 'throughput': '118791.38', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:35:34,933 >> {'loss': 1.7921, 'grad_norm': 0.20523428916931152, 'learning_rate': 1.3068191376065243e-06, 'epoch': 0.8936, 'num_input_tokens_seen': 4685037529, 'completed': '89.36% (1_117 / 1_250)', 'remaining time': '1:17:10', 'throughput': '118450.60', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:36:10,221 >> {'loss': 1.4937, 'grad_norm': 0.18325738608837128, 'learning_rate': 1.3022748307121743e-06, 'epoch': 0.8944, 'num_input_tokens_seen': 4689231833, 'completed': '89.44% (1_118 / 1_250)', 'remaining time': '1:16:35', 'throughput': '118859.91', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:36:45,249 >> {'loss': 1.5632, 'grad_norm': 0.21115408837795258, 'learning_rate': 1.2977632585219296e-06, 'epoch': 0.8952, 'num_input_tokens_seen': 4693426137, 'completed': '89.52% (1_119 / 1_250)', 'remaining time': '1:16:00', 'throughput': '119741.43', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:37:20,299 >> {'loss': 1.8181, 'grad_norm': 0.18315818905830383, 'learning_rate': 1.2932844562179353e-06, 'epoch': 0.896, 'num_input_tokens_seen': 4697620441, 'completed': '89.60% (1_120 / 1_250)', 'remaining time': '1:15:25', 'throughput': '119666.23', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:37:55,372 >> {'loss': 1.7889, 'grad_norm': 0.19947798550128937, 'learning_rate': 1.2888384587267918e-06, 'epoch': 0.8968, 'num_input_tokens_seen': 4701814745, 'completed': '89.68% (1_121 / 1_250)', 'remaining time': '1:14:51', 'throughput': '119587.03', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:38:30,803 >> {'loss': 1.58, 'grad_norm': 0.2136944830417633, 'learning_rate': 1.28442530071928e-06, 'epoch': 0.8976, 'num_input_tokens_seen': 4706009049, 'completed': '89.76% (1_122 / 1_250)', 'remaining time': '1:14:16', 'throughput': '118378.05', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:39:06,293 >> {'loss': 1.8582, 'grad_norm': 0.18188631534576416, 'learning_rate': 1.2800450166100935e-06, 'epoch': 0.8984, 'num_input_tokens_seen': 4710203353, 'completed': '89.84% (1_123 / 1_250)', 'remaining time': '1:13:41', 'throughput': '118184.25', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:39:41,601 >> {'loss': 1.3474, 'grad_norm': 0.15844227373600006, 'learning_rate': 1.2756976405575669e-06, 'epoch': 0.8992, 'num_input_tokens_seen': 4714397657, 'completed': '89.92% (1_124 / 1_250)', 'remaining time': '1:13:06', 'throughput': '118790.73', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:40:15,677 >> {'loss': 1.7795, 'grad_norm': 0.34605592489242554, 'learning_rate': 1.2713832064634127e-06, 'epoch': 0.9, 'num_input_tokens_seen': 4718591961, 'completed': '90.00% (1_125 / 1_250)', 'remaining time': '1:12:31', 'throughput': '123087.97', 'gpu_mem_free': '16314MB'} +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:689: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +[INFO|trainer.py:3503] 2026-05-02 12:40:24,483 >> Saving model checkpoint to /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-1125 +[INFO|configuration_utils.py:472] 2026-05-02 12:40:24,484 >> Configuration saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-1125/config.json +[INFO|configuration_utils.py:807] 2026-05-02 12:40:24,485 >> Configuration saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-1125/generation_config.json +[INFO|modeling_utils.py:2807] 2026-05-02 12:40:37,416 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 3 checkpoint shards. You can find where each parameters has been saved in the index located at /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-1125/model.safetensors.index.json. +[INFO|tokenization_utils_base.py:2684] 2026-05-02 12:40:37,418 >> tokenizer config file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-1125/tokenizer_config.json +[INFO|tokenization_utils_base.py:2693] 2026-05-02 12:40:37,418 >> Special tokens file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-1125/special_tokens_map.json +[INFO|tokenization_utils_base.py:2684] 2026-05-02 12:40:47,994 >> tokenizer config file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/tokenizer_config.json +[INFO|tokenization_utils_base.py:2693] 2026-05-02 12:40:47,995 >> Special tokens file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/special_tokens_map.json +[INFO|trainer.py:3595] 2026-05-02 12:40:48,001 >> Deleting older checkpoint [/tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-1000] due to args.save_total_limit +[WARNING|trainer.py:870] 2026-05-02 12:40:49,218 >> Save streaming dataset state: {'epoch': 0, 'sample_in_epoch': 288000, 'num_canonical_nodes': 2, 'shuffle_seed': 42, 'initial_physical_nodes': 2} +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/utils/checkpoint.py:1399: FutureWarning: `torch.cpu.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cpu', args...)` instead. + with device_autocast_ctx, torch.cpu.amp.autocast(**cpu_autocast_kwargs), recompute_context: # type: ignore[attr-defined] +[INFO|trainer.py:175] 2026-05-02 12:41:24,368 >> {'loss': 1.5852, 'grad_norm': 0.3136942684650421, 'learning_rate': 1.2671017479724537e-06, 'epoch': 0.9008, 'num_input_tokens_seen': 4722786265, 'completed': '90.08% (1_126 / 1_250)', 'remaining time': '1:12:00', 'throughput': '61060.61', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:41:59,680 >> {'loss': 1.5523, 'grad_norm': 0.2525073289871216, 'learning_rate': 1.2628532984723649e-06, 'epoch': 0.9016, 'num_input_tokens_seen': 4726980568, 'completed': '90.16% (1_127 / 1_250)', 'remaining time': '1:11:26', 'throughput': '118777.73', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:42:34,488 >> {'loss': 1.6757, 'grad_norm': 0.21518586575984955, 'learning_rate': 1.2586378910934072e-06, 'epoch': 0.9024, 'num_input_tokens_seen': 4731174872, 'completed': '90.24% (1_128 / 1_250)', 'remaining time': '1:10:51', 'throughput': '120499.29', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:43:10,110 >> {'loss': 1.4785, 'grad_norm': 0.18543820083141327, 'learning_rate': 1.2544555587081741e-06, 'epoch': 0.9032, 'num_input_tokens_seen': 4735369176, 'completed': '90.32% (1_129 / 1_250)', 'remaining time': '1:10:16', 'throughput': '117744.52', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:43:45,289 >> {'loss': 1.5128, 'grad_norm': 0.24814024567604065, 'learning_rate': 1.2503063339313357e-06, 'epoch': 0.904, 'num_input_tokens_seen': 4739563480, 'completed': '90.40% (1_130 / 1_250)', 'remaining time': '1:09:41', 'throughput': '119225.81', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:44:16,062 >> {'loss': 1.6949, 'grad_norm': 0.20555229485034943, 'learning_rate': 1.246190249119378e-06, 'epoch': 0.9048, 'num_input_tokens_seen': 4743757784, 'completed': '90.48% (1_131 / 1_250)', 'remaining time': '1:09:06', 'throughput': '136296.91', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:44:51,270 >> {'loss': 1.5669, 'grad_norm': 0.17162178456783295, 'learning_rate': 1.2421073363703587e-06, 'epoch': 0.9056, 'num_input_tokens_seen': 4747952088, 'completed': '90.56% (1_132 / 1_250)', 'remaining time': '1:08:31', 'throughput': '119131.71', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:45:22,303 >> {'loss': 1.6247, 'grad_norm': 0.32660892605781555, 'learning_rate': 1.2380576275236512e-06, 'epoch': 0.9064, 'num_input_tokens_seen': 4752146392, 'completed': '90.64% (1_133 / 1_250)', 'remaining time': '1:07:56', 'throughput': '135155.48', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:45:57,545 >> {'loss': 1.5289, 'grad_norm': 0.27725163102149963, 'learning_rate': 1.2340411541596985e-06, 'epoch': 0.9072, 'num_input_tokens_seen': 4756340696, 'completed': '90.72% (1_134 / 1_250)', 'remaining time': '1:07:21', 'throughput': '119012.79', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:46:31,915 >> {'loss': 1.6116, 'grad_norm': 0.2167019098997116, 'learning_rate': 1.2300579475997657e-06, 'epoch': 0.908, 'num_input_tokens_seen': 4760535000, 'completed': '90.80% (1_135 / 1_250)', 'remaining time': '1:06:46', 'throughput': '122035.51', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:47:06,073 >> {'loss': 1.6291, 'grad_norm': 0.22180266678333282, 'learning_rate': 1.2261080389056997e-06, 'epoch': 0.9088, 'num_input_tokens_seen': 4764729304, 'completed': '90.88% (1_136 / 1_250)', 'remaining time': '1:06:11', 'throughput': '122791.23', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:47:40,053 >> {'loss': 1.6185, 'grad_norm': 0.23034228384494781, 'learning_rate': 1.22219145887968e-06, 'epoch': 0.9096, 'num_input_tokens_seen': 4768923608, 'completed': '90.96% (1_137 / 1_250)', 'remaining time': '1:05:36', 'throughput': '123434.39', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:48:15,541 >> {'loss': 1.6365, 'grad_norm': 0.2622007429599762, 'learning_rate': 1.2183082380639854e-06, 'epoch': 0.9104, 'num_input_tokens_seen': 4773117912, 'completed': '91.04% (1_138 / 1_250)', 'remaining time': '1:05:02', 'throughput': '118188.70', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:48:50,803 >> {'loss': 1.7537, 'grad_norm': 0.1629297137260437, 'learning_rate': 1.2144584067407533e-06, 'epoch': 0.9112, 'num_input_tokens_seen': 4777312216, 'completed': '91.12% (1_139 / 1_250)', 'remaining time': '1:04:27', 'throughput': '118948.14', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:49:26,194 >> {'loss': 1.7154, 'grad_norm': 0.22218109667301178, 'learning_rate': 1.210641994931739e-06, 'epoch': 0.912, 'num_input_tokens_seen': 4781506520, 'completed': '91.20% (1_140 / 1_250)', 'remaining time': '1:03:52', 'throughput': '118512.84', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:50:01,713 >> {'loss': 1.628, 'grad_norm': 0.343772292137146, 'learning_rate': 1.20685903239809e-06, 'epoch': 0.9128, 'num_input_tokens_seen': 4785700824, 'completed': '91.28% (1_141 / 1_250)', 'remaining time': '1:03:17', 'throughput': '118084.72', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:50:36,967 >> {'loss': 1.7082, 'grad_norm': 0.2805919647216797, 'learning_rate': 1.203109548640107e-06, 'epoch': 0.9136, 'num_input_tokens_seen': 4789895128, 'completed': '91.36% (1_142 / 1_250)', 'remaining time': '1:02:42', 'throughput': '118975.64', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:51:12,269 >> {'loss': 1.5641, 'grad_norm': 0.16993175446987152, 'learning_rate': 1.1993935728970186e-06, 'epoch': 0.9144, 'num_input_tokens_seen': 4794089432, 'completed': '91.44% (1_143 / 1_250)', 'remaining time': '1:02:08', 'throughput': '118811.35', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:51:47,257 >> {'loss': 1.6106, 'grad_norm': 0.27349188923835754, 'learning_rate': 1.1957111341467493e-06, 'epoch': 0.9152, 'num_input_tokens_seen': 4798283736, 'completed': '91.52% (1_144 / 1_250)', 'remaining time': '1:01:33', 'throughput': '119879.91', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:52:22,837 >> {'loss': 1.4972, 'grad_norm': 0.42561066150665283, 'learning_rate': 1.1920622611056976e-06, 'epoch': 0.916, 'num_input_tokens_seen': 4802478040, 'completed': '91.60% (1_145 / 1_250)', 'remaining time': '1:00:58', 'throughput': '117881.44', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:52:58,190 >> {'loss': 1.4807, 'grad_norm': 0.17115552723407745, 'learning_rate': 1.1884469822285071e-06, 'epoch': 0.9168, 'num_input_tokens_seen': 4806672344, 'completed': '91.68% (1_146 / 1_250)', 'remaining time': '1:00:23', 'throughput': '118641.69', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:53:33,623 >> {'loss': 1.6202, 'grad_norm': 0.2153337448835373, 'learning_rate': 1.1848653257078489e-06, 'epoch': 0.9176, 'num_input_tokens_seen': 4810866648, 'completed': '91.76% (1_147 / 1_250)', 'remaining time': '0:59:48', 'throughput': '118373.70', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:54:08,793 >> {'loss': 1.8439, 'grad_norm': 0.32320255041122437, 'learning_rate': 1.1813173194742002e-06, 'epoch': 0.9184, 'num_input_tokens_seen': 4815060952, 'completed': '91.84% (1_148 / 1_250)', 'remaining time': '0:59:14', 'throughput': '119256.81', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:54:43,925 >> {'loss': 1.7424, 'grad_norm': 0.3355695307254791, 'learning_rate': 1.1778029911956262e-06, 'epoch': 0.9192, 'num_input_tokens_seen': 4819255256, 'completed': '91.92% (1_149 / 1_250)', 'remaining time': '0:58:39', 'throughput': '119385.97', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:55:19,035 >> {'loss': 1.5779, 'grad_norm': 0.15720713138580322, 'learning_rate': 1.174322368277565e-06, 'epoch': 0.92, 'num_input_tokens_seen': 4823449560, 'completed': '92.00% (1_150 / 1_250)', 'remaining time': '0:58:04', 'throughput': '119461.90', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:55:53,117 >> {'loss': 1.5287, 'grad_norm': 0.31355005502700806, 'learning_rate': 1.1708754778626134e-06, 'epoch': 0.9208, 'num_input_tokens_seen': 4827643864, 'completed': '92.08% (1_151 / 1_250)', 'remaining time': '0:57:29', 'throughput': '123066.93', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:56:28,340 >> {'loss': 1.6908, 'grad_norm': 0.3144960105419159, 'learning_rate': 1.1674623468303155e-06, 'epoch': 0.9216, 'num_input_tokens_seen': 4831838168, 'completed': '92.16% (1_152 / 1_250)', 'remaining time': '0:56:54', 'throughput': '119078.26', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:57:03,613 >> {'loss': 1.6588, 'grad_norm': 0.23008552193641663, 'learning_rate': 1.164083001796952e-06, 'epoch': 0.9224, 'num_input_tokens_seen': 4836032472, 'completed': '92.24% (1_153 / 1_250)', 'remaining time': '0:56:19', 'throughput': '118908.43', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:57:38,948 >> {'loss': 1.5661, 'grad_norm': 0.16395637392997742, 'learning_rate': 1.1607374691153348e-06, 'epoch': 0.9232, 'num_input_tokens_seen': 4840226775, 'completed': '92.32% (1_154 / 1_250)', 'remaining time': '0:55:45', 'throughput': '118703.72', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:58:10,735 >> {'loss': 1.6178, 'grad_norm': 0.22409309446811676, 'learning_rate': 1.1574257748745988e-06, 'epoch': 0.924, 'num_input_tokens_seen': 4844421079, 'completed': '92.40% (1_155 / 1_250)', 'remaining time': '0:55:10', 'throughput': '131950.11', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:58:46,276 >> {'loss': 1.714, 'grad_norm': 0.3412281572818756, 'learning_rate': 1.154147944900002e-06, 'epoch': 0.9248, 'num_input_tokens_seen': 4848615383, 'completed': '92.48% (1_156 / 1_250)', 'remaining time': '0:54:35', 'throughput': '118011.96', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:59:21,305 >> {'loss': 1.6973, 'grad_norm': 0.18369600176811218, 'learning_rate': 1.1509040047527209e-06, 'epoch': 0.9256, 'num_input_tokens_seen': 4852809687, 'completed': '92.56% (1_157 / 1_250)', 'remaining time': '0:54:00', 'throughput': '119736.99', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 12:59:56,761 >> {'loss': 1.4896, 'grad_norm': 0.1750795692205429, 'learning_rate': 1.1476939797296523e-06, 'epoch': 0.9264, 'num_input_tokens_seen': 4857003991, 'completed': '92.64% (1_158 / 1_250)', 'remaining time': '0:53:25', 'throughput': '118297.32', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:00:28,146 >> {'loss': 1.5927, 'grad_norm': 0.28409090638160706, 'learning_rate': 1.1445178948632163e-06, 'epoch': 0.9272, 'num_input_tokens_seen': 4861198295, 'completed': '92.72% (1_159 / 1_250)', 'remaining time': '0:52:50', 'throughput': '133640.88', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:01:03,323 >> {'loss': 1.5592, 'grad_norm': 0.21625421941280365, 'learning_rate': 1.1413757749211602e-06, 'epoch': 0.928, 'num_input_tokens_seen': 4865392599, 'completed': '92.80% (1_160 / 1_250)', 'remaining time': '0:52:15', 'throughput': '119232.80', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:01:34,224 >> {'loss': 1.6323, 'grad_norm': 0.1743459850549698, 'learning_rate': 1.138267644406367e-06, 'epoch': 0.9288, 'num_input_tokens_seen': 4869586903, 'completed': '92.88% (1_161 / 1_250)', 'remaining time': '0:51:40', 'throughput': '135736.34', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:02:04,957 >> {'loss': 1.5507, 'grad_norm': 0.1830027997493744, 'learning_rate': 1.1351935275566623e-06, 'epoch': 0.9296, 'num_input_tokens_seen': 4873781207, 'completed': '92.96% (1_162 / 1_250)', 'remaining time': '0:51:05', 'throughput': '136471.71', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:02:36,149 >> {'loss': 1.5115, 'grad_norm': 0.23457078635692596, 'learning_rate': 1.1321534483446275e-06, 'epoch': 0.9304, 'num_input_tokens_seen': 4877975511, 'completed': '93.04% (1_163 / 1_250)', 'remaining time': '0:50:30', 'throughput': '134470.47', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:03:10,441 >> {'loss': 1.5057, 'grad_norm': 0.21464906632900238, 'learning_rate': 1.1291474304774102e-06, 'epoch': 0.9312, 'num_input_tokens_seen': 4882169815, 'completed': '93.12% (1_164 / 1_250)', 'remaining time': '0:49:55', 'throughput': '122308.92', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:03:45,634 >> {'loss': 1.5612, 'grad_norm': 0.17906370759010315, 'learning_rate': 1.1261754973965424e-06, 'epoch': 0.932, 'num_input_tokens_seen': 4886364119, 'completed': '93.20% (1_165 / 1_250)', 'remaining time': '0:49:20', 'throughput': '119181.79', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:04:20,937 >> {'loss': 1.7173, 'grad_norm': 0.21542538702487946, 'learning_rate': 1.1232376722777541e-06, 'epoch': 0.9328, 'num_input_tokens_seen': 4890558423, 'completed': '93.28% (1_166 / 1_250)', 'remaining time': '0:48:45', 'throughput': '118809.12', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:04:55,776 >> {'loss': 1.692, 'grad_norm': 0.19832223653793335, 'learning_rate': 1.1203339780307974e-06, 'epoch': 0.9336, 'num_input_tokens_seen': 4894752726, 'completed': '93.36% (1_167 / 1_250)', 'remaining time': '0:48:10', 'throughput': '120389.90', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:05:30,894 >> {'loss': 1.4648, 'grad_norm': 0.17959542572498322, 'learning_rate': 1.1174644372992618e-06, 'epoch': 0.9344, 'num_input_tokens_seen': 4898947030, 'completed': '93.44% (1_168 / 1_250)', 'remaining time': '0:47:36', 'throughput': '119434.34', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:06:05,322 >> {'loss': 1.5533, 'grad_norm': 0.1573592573404312, 'learning_rate': 1.1146290724604025e-06, 'epoch': 0.9352, 'num_input_tokens_seen': 4903141334, 'completed': '93.52% (1_169 / 1_250)', 'remaining time': '0:47:01', 'throughput': '121828.05', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:06:40,588 >> {'loss': 1.5867, 'grad_norm': 0.17400702834129333, 'learning_rate': 1.1118279056249655e-06, 'epoch': 0.936, 'num_input_tokens_seen': 4907335638, 'completed': '93.60% (1_170 / 1_250)', 'remaining time': '0:46:26', 'throughput': '118932.71', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:07:15,678 >> {'loss': 1.6843, 'grad_norm': 0.1922331601381302, 'learning_rate': 1.1090609586370115e-06, 'epoch': 0.9368, 'num_input_tokens_seen': 4911529942, 'completed': '93.68% (1_171 / 1_250)', 'remaining time': '0:45:51', 'throughput': '119532.47', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:07:51,060 >> {'loss': 1.7719, 'grad_norm': 0.16530463099479675, 'learning_rate': 1.1063282530737486e-06, 'epoch': 0.9376, 'num_input_tokens_seen': 4915724246, 'completed': '93.76% (1_172 / 1_250)', 'remaining time': '0:45:16', 'throughput': '118541.81', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:08:26,477 >> {'loss': 1.8961, 'grad_norm': 0.23734091222286224, 'learning_rate': 1.1036298102453635e-06, 'epoch': 0.9384, 'num_input_tokens_seen': 4919918550, 'completed': '93.84% (1_173 / 1_250)', 'remaining time': '0:44:42', 'throughput': '118427.64', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:09:01,616 >> {'loss': 1.4654, 'grad_norm': 0.17715348303318024, 'learning_rate': 1.1009656511948571e-06, 'epoch': 0.9392, 'num_input_tokens_seen': 4924112854, 'completed': '93.92% (1_174 / 1_250)', 'remaining time': '0:44:07', 'throughput': '119361.82', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:09:36,964 >> {'loss': 1.7113, 'grad_norm': 0.16365495324134827, 'learning_rate': 1.0983357966978747e-06, 'epoch': 0.94, 'num_input_tokens_seen': 4928307158, 'completed': '94.00% (1_175 / 1_250)', 'remaining time': '0:43:32', 'throughput': '118656.57', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:10:12,760 >> {'loss': 1.5732, 'grad_norm': 0.2505810856819153, 'learning_rate': 1.0957402672625514e-06, 'epoch': 0.9408, 'num_input_tokens_seen': 4932501462, 'completed': '94.08% (1_176 / 1_250)', 'remaining time': '0:42:57', 'throughput': '117174.34', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:10:47,556 >> {'loss': 1.4771, 'grad_norm': 0.2685171961784363, 'learning_rate': 1.0931790831293472e-06, 'epoch': 0.9416, 'num_input_tokens_seen': 4936695766, 'completed': '94.16% (1_177 / 1_250)', 'remaining time': '0:42:22', 'throughput': '120538.28', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:11:22,981 >> {'loss': 1.4986, 'grad_norm': 0.1951478123664856, 'learning_rate': 1.0906522642708892e-06, 'epoch': 0.9424, 'num_input_tokens_seen': 4940890070, 'completed': '94.24% (1_178 / 1_250)', 'remaining time': '0:41:48', 'throughput': '118400.13', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:11:57,886 >> {'loss': 1.7569, 'grad_norm': 0.18062931299209595, 'learning_rate': 1.0881598303918196e-06, 'epoch': 0.9432, 'num_input_tokens_seen': 4945084374, 'completed': '94.32% (1_179 / 1_250)', 'remaining time': '0:41:13', 'throughput': '120162.55', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:12:31,916 >> {'loss': 1.5207, 'grad_norm': 0.22958685457706451, 'learning_rate': 1.0857018009286382e-06, 'epoch': 0.944, 'num_input_tokens_seen': 4949278678, 'completed': '94.40% (1_180 / 1_250)', 'remaining time': '0:40:38', 'throughput': '123253.65', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:13:07,178 >> {'loss': 1.4568, 'grad_norm': 0.25767308473587036, 'learning_rate': 1.0832781950495521e-06, 'epoch': 0.9448, 'num_input_tokens_seen': 4953472982, 'completed': '94.48% (1_181 / 1_250)', 'remaining time': '0:40:03', 'throughput': '118947.29', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:13:38,049 >> {'loss': 1.7638, 'grad_norm': 0.18853352963924408, 'learning_rate': 1.0808890316543273e-06, 'epoch': 0.9456, 'num_input_tokens_seen': 4957667286, 'completed': '94.56% (1_182 / 1_250)', 'remaining time': '0:39:28', 'throughput': '135867.38', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:14:13,644 >> {'loss': 1.6994, 'grad_norm': 0.17762736976146698, 'learning_rate': 1.0785343293741398e-06, 'epoch': 0.9464, 'num_input_tokens_seen': 4961861590, 'completed': '94.64% (1_183 / 1_250)', 'remaining time': '0:38:53', 'throughput': '117833.04', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:14:49,142 >> {'loss': 1.5871, 'grad_norm': 0.17012125253677368, 'learning_rate': 1.0762141065714308e-06, 'epoch': 0.9472, 'num_input_tokens_seen': 4966055894, 'completed': '94.72% (1_184 / 1_250)', 'remaining time': '0:38:18', 'throughput': '118155.76', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:15:20,256 >> {'loss': 1.7492, 'grad_norm': 0.18150947988033295, 'learning_rate': 1.073928381339764e-06, 'epoch': 0.948, 'num_input_tokens_seen': 4970250198, 'completed': '94.80% (1_185 / 1_250)', 'remaining time': '0:37:43', 'throughput': '134802.63', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:15:55,755 >> {'loss': 1.4154, 'grad_norm': 0.16240836679935455, 'learning_rate': 1.0716771715036834e-06, 'epoch': 0.9488, 'num_input_tokens_seen': 4974444502, 'completed': '94.88% (1_186 / 1_250)', 'remaining time': '0:37:09', 'throughput': '118154.96', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:16:31,041 >> {'loss': 1.3926, 'grad_norm': 0.20899736881256104, 'learning_rate': 1.0694604946185762e-06, 'epoch': 0.9496, 'num_input_tokens_seen': 4978638806, 'completed': '94.96% (1_187 / 1_250)', 'remaining time': '0:36:34', 'throughput': '118863.97', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:17:06,287 >> {'loss': 1.6854, 'grad_norm': 0.1994754821062088, 'learning_rate': 1.0672783679705332e-06, 'epoch': 0.9504, 'num_input_tokens_seen': 4982833110, 'completed': '95.04% (1_188 / 1_250)', 'remaining time': '0:35:59', 'throughput': '119000.75', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:17:41,621 >> {'loss': 1.6379, 'grad_norm': 0.148538276553154, 'learning_rate': 1.0651308085762178e-06, 'epoch': 0.9512, 'num_input_tokens_seen': 4987027414, 'completed': '95.12% (1_189 / 1_250)', 'remaining time': '0:35:24', 'throughput': '118705.66', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:18:17,052 >> {'loss': 1.7795, 'grad_norm': 0.17956824600696564, 'learning_rate': 1.0630178331827281e-06, 'epoch': 0.952, 'num_input_tokens_seen': 4991221718, 'completed': '95.20% (1_190 / 1_250)', 'remaining time': '0:34:49', 'throughput': '118380.08', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:18:51,986 >> {'loss': 1.5095, 'grad_norm': 0.16497643291950226, 'learning_rate': 1.0609394582674713e-06, 'epoch': 0.9528, 'num_input_tokens_seen': 4995416022, 'completed': '95.28% (1_191 / 1_250)', 'remaining time': '0:34:15', 'throughput': '120064.35', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:19:27,490 >> {'loss': 1.5264, 'grad_norm': 0.17523251473903656, 'learning_rate': 1.0588957000380324e-06, 'epoch': 0.9536, 'num_input_tokens_seen': 4999610326, 'completed': '95.36% (1_192 / 1_250)', 'remaining time': '0:33:40', 'throughput': '118136.70', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:20:01,831 >> {'loss': 1.5309, 'grad_norm': 0.14927728474140167, 'learning_rate': 1.0568865744320484e-06, 'epoch': 0.9544, 'num_input_tokens_seen': 5003804630, 'completed': '95.44% (1_193 / 1_250)', 'remaining time': '0:33:05', 'throughput': '122135.86', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:20:37,100 >> {'loss': 1.5121, 'grad_norm': 0.20914320647716522, 'learning_rate': 1.0549120971170852e-06, 'epoch': 0.9552, 'num_input_tokens_seen': 5007998934, 'completed': '95.52% (1_194 / 1_250)', 'remaining time': '0:32:30', 'throughput': '118921.68', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:21:12,368 >> {'loss': 1.5173, 'grad_norm': 0.16009007394313812, 'learning_rate': 1.0529722834905126e-06, 'epoch': 0.956, 'num_input_tokens_seen': 5012193238, 'completed': '95.60% (1_195 / 1_250)', 'remaining time': '0:31:55', 'throughput': '118927.15', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:21:43,274 >> {'loss': 1.6436, 'grad_norm': 0.16726820170879364, 'learning_rate': 1.0510671486793874e-06, 'epoch': 0.9568, 'num_input_tokens_seen': 5016387542, 'completed': '95.68% (1_196 / 1_250)', 'remaining time': '0:31:20', 'throughput': '135712.38', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:22:18,544 >> {'loss': 1.5163, 'grad_norm': 0.2087308168411255, 'learning_rate': 1.0491967075403334e-06, 'epoch': 0.9576, 'num_input_tokens_seen': 5020581846, 'completed': '95.76% (1_197 / 1_250)', 'remaining time': '0:30:45', 'throughput': '118918.60', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:22:53,701 >> {'loss': 1.6095, 'grad_norm': 0.1644551157951355, 'learning_rate': 1.0473609746594258e-06, 'epoch': 0.9584, 'num_input_tokens_seen': 5024776150, 'completed': '95.84% (1_198 / 1_250)', 'remaining time': '0:30:11', 'throughput': '119302.79', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:23:27,616 >> {'loss': 1.5221, 'grad_norm': 0.17127752304077148, 'learning_rate': 1.0455599643520792e-06, 'epoch': 0.9592, 'num_input_tokens_seen': 5028970454, 'completed': '95.92% (1_199 / 1_250)', 'remaining time': '0:29:36', 'throughput': '123671.04', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:24:00,837 >> {'loss': 1.6369, 'grad_norm': 0.2019064575433731, 'learning_rate': 1.0437936906629336e-06, 'epoch': 0.96, 'num_input_tokens_seen': 5033164758, 'completed': '96.00% (1_200 / 1_250)', 'remaining time': '0:29:01', 'throughput': '126255.67', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:24:36,132 >> {'loss': 1.8002, 'grad_norm': 0.18915867805480957, 'learning_rate': 1.0420621673657463e-06, 'epoch': 0.9608, 'num_input_tokens_seen': 5037359062, 'completed': '96.08% (1_201 / 1_250)', 'remaining time': '0:28:26', 'throughput': '118834.72', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:25:11,425 >> {'loss': 1.7776, 'grad_norm': 0.16429775953292847, 'learning_rate': 1.040365407963283e-06, 'epoch': 0.9616, 'num_input_tokens_seen': 5041553366, 'completed': '96.16% (1_202 / 1_250)', 'remaining time': '0:27:51', 'throughput': '118842.66', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:25:46,821 >> {'loss': 1.5173, 'grad_norm': 0.18383543193340302, 'learning_rate': 1.0387034256872147e-06, 'epoch': 0.9624, 'num_input_tokens_seen': 5045747670, 'completed': '96.24% (1_203 / 1_250)', 'remaining time': '0:27:16', 'throughput': '118495.63', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:26:18,285 >> {'loss': 1.6743, 'grad_norm': 0.17809517681598663, 'learning_rate': 1.0370762334980129e-06, 'epoch': 0.9632, 'num_input_tokens_seen': 5049941974, 'completed': '96.32% (1_204 / 1_250)', 'remaining time': '0:26:41', 'throughput': '133304.74', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:26:53,725 >> {'loss': 1.3512, 'grad_norm': 0.1321393847465515, 'learning_rate': 1.0354838440848502e-06, 'epoch': 0.964, 'num_input_tokens_seen': 5054136278, 'completed': '96.40% (1_205 / 1_250)', 'remaining time': '0:26:07', 'throughput': '118352.12', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:27:29,203 >> {'loss': 1.5702, 'grad_norm': 0.1900843232870102, 'learning_rate': 1.0339262698654973e-06, 'epoch': 0.9648, 'num_input_tokens_seen': 5058330582, 'completed': '96.48% (1_206 / 1_250)', 'remaining time': '0:25:32', 'throughput': '118220.67', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:28:02,800 >> {'loss': 1.7484, 'grad_norm': 0.16905565559864044, 'learning_rate': 1.0324035229862328e-06, 'epoch': 0.9656, 'num_input_tokens_seen': 5062524886, 'completed': '96.56% (1_207 / 1_250)', 'remaining time': '0:24:57', 'throughput': '124841.67', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:28:37,937 >> {'loss': 1.5167, 'grad_norm': 0.2337808907032013, 'learning_rate': 1.030915615321741e-06, 'epoch': 0.9664, 'num_input_tokens_seen': 5066719190, 'completed': '96.64% (1_208 / 1_250)', 'remaining time': '0:24:22', 'throughput': '119368.90', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:29:13,295 >> {'loss': 1.5361, 'grad_norm': 0.1650080382823944, 'learning_rate': 1.0294625584750262e-06, 'epoch': 0.9672, 'num_input_tokens_seen': 5070913494, 'completed': '96.72% (1_209 / 1_250)', 'remaining time': '0:23:47', 'throughput': '118625.61', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:29:48,594 >> {'loss': 1.4783, 'grad_norm': 0.17270877957344055, 'learning_rate': 1.0280443637773165e-06, 'epoch': 0.968, 'num_input_tokens_seen': 5075107797, 'completed': '96.80% (1_210 / 1_250)', 'remaining time': '0:23:13', 'throughput': '118820.97', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:30:23,936 >> {'loss': 1.6341, 'grad_norm': 0.16395287215709686, 'learning_rate': 1.0266610422879793e-06, 'epoch': 0.9688, 'num_input_tokens_seen': 5079302101, 'completed': '96.88% (1_211 / 1_250)', 'remaining time': '0:22:38', 'throughput': '118677.86', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:30:59,416 >> {'loss': 1.7798, 'grad_norm': 1.3473514318466187, 'learning_rate': 1.0253126047944342e-06, 'epoch': 0.9696, 'num_input_tokens_seen': 5083496404, 'completed': '96.96% (1_212 / 1_250)', 'remaining time': '0:22:03', 'throughput': '118216.82', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:31:34,418 >> {'loss': 1.5935, 'grad_norm': 0.18852022290229797, 'learning_rate': 1.0239990618120667e-06, 'epoch': 0.9704, 'num_input_tokens_seen': 5087690708, 'completed': '97.04% (1_213 / 1_250)', 'remaining time': '0:21:28', 'throughput': '119829.69', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:32:05,152 >> {'loss': 1.5286, 'grad_norm': 0.4547899067401886, 'learning_rate': 1.0227204235841493e-06, 'epoch': 0.9712, 'num_input_tokens_seen': 5091885012, 'completed': '97.12% (1_214 / 1_250)', 'remaining time': '0:20:53', 'throughput': '136472.79', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:32:38,751 >> {'loss': 1.5475, 'grad_norm': 0.16574302315711975, 'learning_rate': 1.0214767000817597e-06, 'epoch': 0.972, 'num_input_tokens_seen': 5096079316, 'completed': '97.20% (1_215 / 1_250)', 'remaining time': '0:20:18', 'throughput': '124834.89', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:33:13,088 >> {'loss': 1.3926, 'grad_norm': 0.14527054131031036, 'learning_rate': 1.0202679010037038e-06, 'epoch': 0.9728, 'num_input_tokens_seen': 5100273620, 'completed': '97.28% (1_216 / 1_250)', 'remaining time': '0:19:43', 'throughput': '122149.88', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:33:48,303 >> {'loss': 1.6118, 'grad_norm': 0.25012287497520447, 'learning_rate': 1.0190940357764393e-06, 'epoch': 0.9736, 'num_input_tokens_seen': 5104467924, 'completed': '97.36% (1_217 / 1_250)', 'remaining time': '0:19:09', 'throughput': '119105.95', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:34:22,090 >> {'loss': 1.6132, 'grad_norm': 0.18459345400333405, 'learning_rate': 1.0179551135540031e-06, 'epoch': 0.9744, 'num_input_tokens_seen': 5108662228, 'completed': '97.44% (1_218 / 1_250)', 'remaining time': '0:18:34', 'throughput': '124139.01', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:34:57,545 >> {'loss': 1.4707, 'grad_norm': 0.20083102583885193, 'learning_rate': 1.0168511432179393e-06, 'epoch': 0.9752, 'num_input_tokens_seen': 5112856532, 'completed': '97.52% (1_219 / 1_250)', 'remaining time': '0:17:59', 'throughput': '118297.74', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:35:32,549 >> {'loss': 1.7141, 'grad_norm': 0.22948502004146576, 'learning_rate': 1.0157821333772305e-06, 'epoch': 0.976, 'num_input_tokens_seen': 5117050836, 'completed': '97.60% (1_220 / 1_250)', 'remaining time': '0:17:24', 'throughput': '119825.63', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:36:04,200 >> {'loss': 1.575, 'grad_norm': 0.16975972056388855, 'learning_rate': 1.0147480923682308e-06, 'epoch': 0.9768, 'num_input_tokens_seen': 5121245140, 'completed': '97.68% (1_221 / 1_250)', 'remaining time': '0:16:49', 'throughput': '132514.77', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:36:39,665 >> {'loss': 1.5256, 'grad_norm': 0.1627933382987976, 'learning_rate': 1.0137490282545987e-06, 'epoch': 0.9776, 'num_input_tokens_seen': 5125439444, 'completed': '97.76% (1_222 / 1_250)', 'remaining time': '0:16:15', 'throughput': '118267.11', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:37:15,127 >> {'loss': 1.376, 'grad_norm': 0.1695386916399002, 'learning_rate': 1.0127849488272375e-06, 'epoch': 0.9784, 'num_input_tokens_seen': 5129633747, 'completed': '97.84% (1_223 / 1_250)', 'remaining time': '0:15:40', 'throughput': '118275.00', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:37:50,429 >> {'loss': 1.7587, 'grad_norm': 0.2152308076620102, 'learning_rate': 1.0118558616042317e-06, 'epoch': 0.9792, 'num_input_tokens_seen': 5133828051, 'completed': '97.92% (1_224 / 1_250)', 'remaining time': '0:15:05', 'throughput': '118814.34', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:38:25,935 >> {'loss': 1.5566, 'grad_norm': 0.1837107241153717, 'learning_rate': 1.0109617738307914e-06, 'epoch': 0.98, 'num_input_tokens_seen': 5138022355, 'completed': '98.00% (1_225 / 1_250)', 'remaining time': '0:14:30', 'throughput': '118128.70', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:39:01,153 >> {'loss': 1.7843, 'grad_norm': 0.16883346438407898, 'learning_rate': 1.0101026924791904e-06, 'epoch': 0.9808, 'num_input_tokens_seen': 5142216659, 'completed': '98.08% (1_226 / 1_250)', 'remaining time': '0:13:55', 'throughput': '119095.33', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:39:33,826 >> {'loss': 1.5666, 'grad_norm': 0.21837717294692993, 'learning_rate': 1.0092786242487202e-06, 'epoch': 0.9816, 'num_input_tokens_seen': 5146410963, 'completed': '98.16% (1_227 / 1_250)', 'remaining time': '0:13:20', 'throughput': '128372.65', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:40:04,733 >> {'loss': 1.6577, 'grad_norm': 0.26251280307769775, 'learning_rate': 1.0084895755656282e-06, 'epoch': 0.9824, 'num_input_tokens_seen': 5150605267, 'completed': '98.24% (1_228 / 1_250)', 'remaining time': '0:12:46', 'throughput': '135708.93', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:40:39,682 >> {'loss': 1.5901, 'grad_norm': 0.16117678582668304, 'learning_rate': 1.0077355525830762e-06, 'epoch': 0.9832, 'num_input_tokens_seen': 5154799571, 'completed': '98.32% (1_229 / 1_250)', 'remaining time': '0:12:11', 'throughput': '120011.70', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:41:15,070 >> {'loss': 1.6919, 'grad_norm': 0.17492586374282837, 'learning_rate': 1.0070165611810856e-06, 'epoch': 0.984, 'num_input_tokens_seen': 5158993875, 'completed': '98.40% (1_230 / 1_250)', 'remaining time': '0:11:36', 'throughput': '118522.56', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:41:50,098 >> {'loss': 1.4087, 'grad_norm': 0.23041006922721863, 'learning_rate': 1.0063326069664967e-06, 'epoch': 0.9848, 'num_input_tokens_seen': 5163188179, 'completed': '98.48% (1_231 / 1_250)', 'remaining time': '0:11:01', 'throughput': '119739.91', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:42:24,889 >> {'loss': 1.6045, 'grad_norm': 0.18723750114440918, 'learning_rate': 1.0056836952729216e-06, 'epoch': 0.9856, 'num_input_tokens_seen': 5167382483, 'completed': '98.56% (1_232 / 1_250)', 'remaining time': '0:10:26', 'throughput': '120557.61', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:43:00,204 >> {'loss': 1.6929, 'grad_norm': 0.2323579043149948, 'learning_rate': 1.0050698311607034e-06, 'epoch': 0.9864, 'num_input_tokens_seen': 5171576787, 'completed': '98.64% (1_233 / 1_250)', 'remaining time': '0:09:51', 'throughput': '118770.35', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:43:35,349 >> {'loss': 1.6386, 'grad_norm': 0.22705872356891632, 'learning_rate': 1.004491019416879e-06, 'epoch': 0.9872, 'num_input_tokens_seen': 5175771091, 'completed': '98.72% (1_234 / 1_250)', 'remaining time': '0:09:17', 'throughput': '119342.68', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:44:10,603 >> {'loss': 1.5095, 'grad_norm': 0.17357122898101807, 'learning_rate': 1.0039472645551373e-06, 'epoch': 0.988, 'num_input_tokens_seen': 5179965395, 'completed': '98.80% (1_235 / 1_250)', 'remaining time': '0:08:42', 'throughput': '118972.44', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:44:46,052 >> {'loss': 1.371, 'grad_norm': 0.15724295377731323, 'learning_rate': 1.0034385708157892e-06, 'epoch': 0.9888, 'num_input_tokens_seen': 5184159699, 'completed': '98.88% (1_236 / 1_250)', 'remaining time': '0:08:07', 'throughput': '118319.87', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:45:21,368 >> {'loss': 1.8358, 'grad_norm': 0.18532343208789825, 'learning_rate': 1.0029649421657297e-06, 'epoch': 0.9896, 'num_input_tokens_seen': 5188354003, 'completed': '98.96% (1_237 / 1_250)', 'remaining time': '0:07:32', 'throughput': '118764.02', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:45:55,600 >> {'loss': 1.6718, 'grad_norm': 0.26857542991638184, 'learning_rate': 1.002526382298411e-06, 'epoch': 0.9904, 'num_input_tokens_seen': 5192548307, 'completed': '99.04% (1_238 / 1_250)', 'remaining time': '0:06:57', 'throughput': '122528.28', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:46:26,964 >> {'loss': 1.6728, 'grad_norm': 0.15345017611980438, 'learning_rate': 1.0021228946338101e-06, 'epoch': 0.9912, 'num_input_tokens_seen': 5196742611, 'completed': '99.12% (1_239 / 1_250)', 'remaining time': '0:06:22', 'throughput': '133726.16', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:47:02,252 >> {'loss': 1.5705, 'grad_norm': 0.21973149478435516, 'learning_rate': 1.0017544823184055e-06, 'epoch': 0.992, 'num_input_tokens_seen': 5200936915, 'completed': '99.20% (1_240 / 1_250)', 'remaining time': '0:05:48', 'throughput': '118860.50', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:47:37,841 >> {'loss': 1.8467, 'grad_norm': 0.17794884741306305, 'learning_rate': 1.0014211482251504e-06, 'epoch': 0.9928, 'num_input_tokens_seen': 5205131219, 'completed': '99.28% (1_241 / 1_250)', 'remaining time': '0:05:13', 'throughput': '117855.53', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:48:12,273 >> {'loss': 1.5522, 'grad_norm': 0.17867451906204224, 'learning_rate': 1.0011228949534504e-06, 'epoch': 0.9936, 'num_input_tokens_seen': 5209325523, 'completed': '99.36% (1_242 / 1_250)', 'remaining time': '0:04:38', 'throughput': '121811.61', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:48:47,747 >> {'loss': 1.5856, 'grad_norm': 0.15247677266597748, 'learning_rate': 1.0008597248291451e-06, 'epoch': 0.9944, 'num_input_tokens_seen': 5213519827, 'completed': '99.44% (1_243 / 1_250)', 'remaining time': '0:04:03', 'throughput': '118236.53', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:49:19,373 >> {'loss': 1.7437, 'grad_norm': 0.1713363528251648, 'learning_rate': 1.0006316399044886e-06, 'epoch': 0.9952, 'num_input_tokens_seen': 5217714131, 'completed': '99.52% (1_244 / 1_250)', 'remaining time': '0:03:28', 'throughput': '132624.00', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:49:54,732 >> {'loss': 1.6497, 'grad_norm': 0.20595428347587585, 'learning_rate': 1.0004386419581311e-06, 'epoch': 0.996, 'num_input_tokens_seen': 5221908435, 'completed': '99.60% (1_245 / 1_250)', 'remaining time': '0:02:54', 'throughput': '118619.23', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:50:25,503 >> {'loss': 1.601, 'grad_norm': 0.17313897609710693, 'learning_rate': 1.000280732495111e-06, 'epoch': 0.9968, 'num_input_tokens_seen': 5226102739, 'completed': '99.68% (1_246 / 1_250)', 'remaining time': '0:02:19', 'throughput': '136305.59', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:51:01,176 >> {'loss': 1.5026, 'grad_norm': 0.16923101246356964, 'learning_rate': 1.0001579127468374e-06, 'epoch': 0.9976, 'num_input_tokens_seen': 5230297043, 'completed': '99.76% (1_247 / 1_250)', 'remaining time': '0:01:44', 'throughput': '117578.98', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:51:36,383 >> {'loss': 1.5055, 'grad_norm': 0.16900338232517242, 'learning_rate': 1.000070183671083e-06, 'epoch': 0.9984, 'num_input_tokens_seen': 5234491347, 'completed': '99.84% (1_248 / 1_250)', 'remaining time': '0:01:09', 'throughput': '119131.33', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:52:08,014 >> {'loss': 1.5654, 'grad_norm': 0.15808485448360443, 'learning_rate': 1.0000175459519775e-06, 'epoch': 0.9992, 'num_input_tokens_seen': 5238685651, 'completed': '99.92% (1_249 / 1_250)', 'remaining time': '0:00:34', 'throughput': '132599.14', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:175] 2026-05-02 13:52:38,540 >> {'loss': 1.8211, 'grad_norm': 0.20161443948745728, 'learning_rate': 1.0000000000000002e-06, 'epoch': 1.0, 'num_input_tokens_seen': 5242879955, 'completed': '100.00% (1_250 / 1_250)', 'remaining time': '0:00:00', 'throughput': '137403.63', 'gpu_mem_free': '16314MB'} +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:689: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +[INFO|trainer.py:3503] 2026-05-02 13:52:47,051 >> Saving model checkpoint to /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-1250 +[INFO|configuration_utils.py:472] 2026-05-02 13:52:47,053 >> Configuration saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-1250/config.json +[INFO|configuration_utils.py:807] 2026-05-02 13:52:47,053 >> Configuration saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-1250/generation_config.json +[INFO|modeling_utils.py:2807] 2026-05-02 13:52:59,361 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 3 checkpoint shards. You can find where each parameters has been saved in the index located at /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-1250/model.safetensors.index.json. +[INFO|tokenization_utils_base.py:2684] 2026-05-02 13:52:59,363 >> tokenizer config file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-1250/tokenizer_config.json +[INFO|tokenization_utils_base.py:2693] 2026-05-02 13:52:59,363 >> Special tokens file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-1250/special_tokens_map.json +[INFO|tokenization_utils_base.py:2684] 2026-05-02 13:53:09,230 >> tokenizer config file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/tokenizer_config.json +[INFO|tokenization_utils_base.py:2693] 2026-05-02 13:53:09,230 >> Special tokens file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/special_tokens_map.json +[INFO|trainer.py:3595] 2026-05-02 13:53:09,235 >> Deleting older checkpoint [/tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/checkpoint-1125] due to args.save_total_limit +[WARNING|trainer.py:870] 2026-05-02 13:53:10,320 >> Save streaming dataset state: {'epoch': 0, 'sample_in_epoch': 320000, 'num_canonical_nodes': 2, 'shuffle_seed': 42, 'initial_physical_nodes': 2} +[INFO|trainer.py:2394] 2026-05-02 13:53:10,353 >> + +Training completed. Do not forget to share your model on huggingface.co/models =) + + +[INFO|trainer.py:175] 2026-05-02 13:53:10,356 >> {'train_runtime': 43550.4142, 'train_samples_per_second': 7.348, 'train_steps_per_second': 0.029, 'train_loss': 1.6664842562675477, 'epoch': 1.0, 'num_input_tokens_seen': 5242879955, 'completed': '100.00% (1_250 / 1_250)', 'remaining time': '0:00:00', 'throughput': '0.00', 'gpu_mem_free': '16314MB'} +[INFO|trainer.py:4283] 2026-05-02 13:53:10,356 >> Waiting for the current checkpoint push to be finished, this might take a couple of minutes. +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:689: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +[INFO|trainer.py:3503] 2026-05-02 13:54:14,557 >> Saving model checkpoint to /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope +[INFO|configuration_utils.py:472] 2026-05-02 13:54:14,564 >> Configuration saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/config.json +[INFO|configuration_utils.py:807] 2026-05-02 13:54:14,565 >> Configuration saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/generation_config.json +[INFO|modeling_utils.py:2807] 2026-05-02 13:54:31,082 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 3 checkpoint shards. You can find where each parameters has been saved in the index located at /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/model.safetensors.index.json. +[INFO|tokenization_utils_base.py:2684] 2026-05-02 13:54:31,084 >> tokenizer config file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/tokenizer_config.json +[INFO|tokenization_utils_base.py:2693] 2026-05-02 13:54:31,084 >> Special tokens file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/special_tokens_map.json +/project/flame/aviralku/miniconda3/envs/cope_train/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py:689: FutureWarning: FSDP.state_dict_type() and FSDP.set_state_dict_type() are being deprecated. Please use APIs, get_state_dict() and set_state_dict(), which can support different parallelisms, FSDP1, FSDP2, DDP. API doc: https://pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict.get_state_dict .Tutorial: https://pytorch.org/tutorials/recipes/distributed_checkpoint_recipe.html . + warnings.warn( +[INFO|trainer.py:3503] 2026-05-02 13:54:39,668 >> Saving model checkpoint to /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope +[INFO|configuration_utils.py:472] 2026-05-02 13:54:39,669 >> Configuration saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/config.json +[INFO|configuration_utils.py:807] 2026-05-02 13:54:39,670 >> Configuration saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/generation_config.json +[INFO|modeling_utils.py:2807] 2026-05-02 13:54:56,417 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 3 checkpoint shards. You can find where each parameters has been saved in the index located at /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/model.safetensors.index.json. +[INFO|tokenization_utils_base.py:2684] 2026-05-02 13:54:56,420 >> tokenizer config file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/tokenizer_config.json +[INFO|tokenization_utils_base.py:2693] 2026-05-02 13:54:56,420 >> Special tokens file saved in /tmp/aviralku/checkpoints/lcft_gemma-2b_prolong-gemma-parts_ProLong64KMix_bsz256_steps1250_lr1e-5_warmup0.1_rope200000cope/special_tokens_map.json + Processing Files (0 / 0) : | | 0.00B / 0.00B + New Data Upload : | | 0.00B / 0.00B  + + ...000cope/training_args.bin: 100%|██████████| 5.75kB / 5.75kB  + + + ...00000cope/tokenizer.model: 100%|██████████| 4.24MB / 4.24MB  + + + + ...7ubroa/run-1i7ubroa.wandb: 100%|█████████▉| 12.8MB / 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DEBUG SenderThread:3694372 [sender.py:send_request():406] send_request: status_report +2026-05-02 12:26:49,191 DEBUG HandlerThread:3694372 [handler.py:handle_request():158] handle_request: status_report +2026-05-02 12:26:49,192 DEBUG SenderThread:3694372 [sender.py:send_request():406] send_request: status_report +2026-05-02 12:26:51,856 DEBUG HandlerThread:3694372 [handler.py:handle_request():158] handle_request: partial_history +2026-05-02 12:26:54,193 DEBUG HandlerThread:3694372 [handler.py:handle_request():158] handle_request: status_report +2026-05-02 12:26:54,193 DEBUG SenderThread:3694372 [sender.py:send_request():406] send_request: status_report +2026-05-02 12:26:59,194 DEBUG HandlerThread:3694372 [handler.py:handle_request():158] handle_request: status_report +2026-05-02 12:26:59,194 DEBUG SenderThread:3694372 [sender.py:send_request():406] send_request: status_report +2026-05-02 12:27:04,195 DEBUG HandlerThread:3694372 [handler.py:handle_request():158] handle_request: 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01:47:27,449 INFO MainThread:3693204 [wandb_config.py:__setitem__():151] config set model/num_parameters = 156635776 - > +2026-05-02 01:47:27,449 INFO MainThread:3693204 [wandb_run.py:_config_callback():1382] config_cb model/num_parameters 156635776 None diff --git a/wandb/offline-run-20260502_014721-1i7ubroa/files/conda-environment.yaml b/wandb/offline-run-20260502_014721-1i7ubroa/files/conda-environment.yaml new file mode 100644 index 0000000..216bd7e --- /dev/null +++ b/wandb/offline-run-20260502_014721-1i7ubroa/files/conda-environment.yaml @@ -0,0 +1,142 @@ +name: cope_train +channels: + - defaults +dependencies: + - _libgcc_mutex=0.1=main + - _openmp_mutex=5.1=1_gnu + - bzip2=1.0.8=h5eee18b_6 + - ca-certificates=2026.3.19=h06a4308_0 + - ld_impl_linux-64=2.44=h9e0c5a2_3 + - libexpat=2.7.5=h7354ed3_0 + - libffi=3.4.4=h6a678d5_1 + - libgcc=15.2.0=h69a1729_7 + - libgcc-ng=15.2.0=h166f726_7 + - libgomp=15.2.0=h4751f2c_7 + - libnsl=2.0.0=h5eee18b_0 + - libstdcxx=15.2.0=h39759b7_7 + - 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DEBUG SenderThread:3694372 [sender.py:send_request():406] send_request: status_report +2026-05-02 05:51:12,092 DEBUG HandlerThread:3694372 [handler.py:handle_request():158] handle_request: status_report +2026-05-02 05:51:12,092 DEBUG SenderThread:3694372 [sender.py:send_request():406] send_request: status_report +2026-05-02 05:51:14,245 DEBUG HandlerThread:3694372 [handler.py:handle_request():158] handle_request: partial_history +2026-05-02 05:51:17,094 DEBUG HandlerThread:3694372 [handler.py:handle_request():158] handle_request: status_report +2026-05-02 05:51:17,094 DEBUG SenderThread:3694372 [sender.py:send_request():406] send_request: status_report +2026-05-02 05:51:22,095 DEBUG HandlerThread:3694372 [handler.py:handle_request():158] handle_request: status_report +2026-05-02 05:51:22,095 DEBUG SenderThread:3694372 [sender.py:send_request():406] send_request: status_report +2026-05-02 05:51:27,097 DEBUG HandlerThread:3694372 [handler.py:handle_request():158] handle_request: 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DEBUG SenderThread:3694372 [sender.py:send_request():406] send_request: status_report +2026-05-02 12:28:34,219 DEBUG HandlerThread:3694372 [handler.py:handle_request():158] handle_request: status_report +2026-05-02 12:28:34,220 DEBUG SenderThread:3694372 [sender.py:send_request():406] send_request: status_report +2026-05-02 12:28:38,252 DEBUG HandlerThread:3694372 [handler.py:handle_request():158] handle_request: partial_history +2026-05-02 12:28:39,221 DEBUG HandlerThread:3694372 [handler.py:handle_request():158] handle_request: status_report +2026-05-02 12:28:39,221 DEBUG SenderThread:3694372 [sender.py:send_request():406] send_request: status_report +2026-05-02 12:28:44,222 DEBUG HandlerThread:3694372 [handler.py:handle_request():158] handle_request: status_report +2026-05-02 12:28:44,222 DEBUG SenderThread:3694372 [sender.py:send_request():406] send_request: status_report +2026-05-02 12:28:49,223 DEBUG HandlerThread:3694372 [handler.py:handle_request():158] handle_request: 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