jackf857/llama-3-8b-base-new-dpo-hh-helpful-s_star0.4-4xh200-batch-64-20260421-214335-rerun
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ModelHub XC ab10c6b4c0 初始化项目，由ModelHub XC社区提供模型 
Model: jackf857/llama-3-8b-base-new-dpo-hh-helpful-s_star0.4-4xh200-batch-64-20260421-214335-rerun
Source: Original Platform
2026-05-10 13:35:35 +08:00

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2026-04-21 21:43:42 - INFO - __main__ - Model parameters ModelArguments(base_model_revision=None, model_name_or_path='/root/dynamic-dpo-v4/sft-checkpoints/llama-3-8b-base-sft-hh-helpful-4xh200', model_revision='main', model_code_revision=None, torch_dtype='bfloat16', tokenizer_name_or_path=None, trust_remote_code=False, attn_implementation='flash_attention_2', use_peft=False, lora_r=16, lora_alpha=32, lora_dropout=0.05, lora_target_modules=None, lora_modules_to_save=None, load_in_8bit=False, load_in_4bit=False, bnb_4bit_quant_type='nf4', use_bnb_nested_quant=False, bnb_4bit_quant_storage='uint8')
2026-04-21 21:43:42 - INFO - __main__ - Data parameters DataArguments(chat_template=None, dataset_mixer={'Anthropic/hh-rlhf': 1.0}, text_column='text', dataset_splits=['train', 'test'], dataset_configs=['helpful-base'], dataset_dir=None, preprocessing_num_workers=12, use_persistent_hf_cache=True, hf_cache_dir='/root/dynamic-dpo-v4/hf/datasets', truncation_side=None, auto_insert_empty_system_msg=True, preprocessing_log_samples=0, preprocessing_log_dir=None)
2026-04-21 21:43:42 - INFO - __main__ - Training/evaluation parameters NewDPOConfig(
_n_gpu=1,
accelerator_config={'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None, 'use_configured_state': False},
adafactor=False,
adam_beta1=0.9,
adam_beta2=0.999,
adam_epsilon=1e-08,
auto_find_batch_size=False,
average_tokens_across_devices=False,
batch_eval_metrics=False,
beta=0.1,
bf16=True,
bf16_full_eval=False,
data_seed=None,
dataloader_drop_last=True,
dataloader_num_workers=0,
dataloader_persistent_workers=False,
dataloader_pin_memory=True,
dataloader_prefetch_factor=None,
dataset_num_proc=12,
ddp_backend=None,
ddp_broadcast_buffers=None,
ddp_bucket_cap_mb=None,
ddp_find_unused_parameters=None,
ddp_timeout=1800,
debug=[],
deepspeed=None,
disable_dropout=True,
disable_tqdm=False,
do_eval=True,
do_predict=False,
do_train=False,
eta=0.1,
eval_accumulation_steps=None,
eval_delay=0,
eval_do_concat_batches=True,
eval_on_start=False,
eval_steps=200,
eval_strategy=IntervalStrategy.STEPS,
eval_use_gather_object=False,
f_alpha_divergence_coef=1.0,
f_divergence_type=reverse_kl,
force_use_ref_model=False,
fp16=False,
fp16_backend=auto,
fp16_full_eval=False,
fp16_opt_level=O1,
fsdp=[],
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,
generate_during_eval=False,
gradient_accumulation_steps=2,
gradient_checkpointing=True,
gradient_checkpointing_kwargs={'use_reentrant': False},
greater_is_better=None,
group_by_length=False,
half_precision_backend=auto,
hub_always_push=False,
hub_margin_dataset_id=None,
hub_model_id=jackf857/llama-3-8b-base-new-dpo-hh-helpful-s_star0.4-4xh200-batch-64-20260421-214335-rerun,
hub_model_revision=main,
hub_private_repo=None,
hub_strategy=HubStrategy.EVERY_SAVE,
hub_token=<HUB_TOKEN>,
ignore_data_skip=False,
include_for_metrics=[],
include_inputs_for_metrics=False,
include_num_input_tokens_seen=False,
include_tokens_per_second=False,
is_encoder_decoder=None,
jit_mode_eval=False,
label_names=None,
label_pad_token_id=-100,
label_smoothing=0.0,
label_smoothing_factor=0.0,
learning_rate=5e-07,
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=outputs/llama3-8b-base-new-method-s_star0.4/runs/Apr21_21-43-41_f6a54ae9d6f6,
logging_first_step=True,
logging_nan_inf_filter=True,
logging_steps=5,
logging_strategy=IntervalStrategy.STEPS,
loss_type=sigmoid,
lr_scheduler_kwargs={},
lr_scheduler_type=SchedulerType.COSINE,
margin_dataset_private=None,
margin_dataset_split=train,
margin_log_path=/root/dynamic-dpo-v4/outputs/llama-3-8b-base-new-dpo-hh-helpful-s_star0.4-4xh200-batch-64-20260421-214335-rerun/margin_logs,
margin_log_steps=1,
margin_save_full=True,
max_grad_norm=1.0,
max_length=512,
max_prompt_length=256,
max_steps=-1,
max_target_length=None,
metric_for_best_model=None,
model_adapter_name=None,
model_init_kwargs=None,
mp_parameters=,
neftune_noise_alpha=None,
no_cuda=False,
non_finite_logits_handling=error,
num_train_epochs=1,
optim=OptimizerNames.ADAMW_TORCH,
optim_args=None,
optim_target_modules=None,
output_dir=/root/dynamic-dpo-v4/outputs/llama-3-8b-base-new-dpo-hh-helpful-s_star0.4-4xh200-batch-64-20260421-214335-rerun,
overwrite_output_dir=False,
padding_value=None,
past_index=-1,
per_device_eval_batch_size=8,
per_device_train_batch_size=8,
post_tokenization_log_dir=None,
post_tokenization_log_samples=0,
precompute_ref_batch_size=None,
precompute_ref_eval_batch_size=None,
precompute_ref_log_probs=False,
prediction_loss_only=False,
push_margin_dataset=True,
push_to_hub=True,
push_to_hub_model_id=None,
push_to_hub_organization=None,
push_to_hub_token=<PUSH_TO_HUB_TOKEN>,
q_target=0.45,
ray_scope=last,
ref_adapter_name=None,
ref_model_init_kwargs=None,
ref_model_mixup_alpha=0.9,
ref_model_sync_steps=64,
reference_free=False,
remove_unused_columns=False,
report_to=['wandb'],
require_explicit_ref_model=True,
restore_callback_states_from_checkpoint=False,
resume_from_checkpoint=None,
reuse_tokenized_dataset=True,
rpo_alpha=None,
run_name=llama-3-8b-base-new-dpo-hh-helpful-s_star0.4-4xh200-batch-64-20260421-214335-rerun,
s_star=0.4,
save_on_each_node=False,
save_only_model=False,
save_safetensors=True,
save_steps=50,
save_strategy=SaveStrategy.NO,
save_total_limit=2,
seed=42,
sft_weight=0.0,
skip_memory_metrics=True,
sync_ref_model=False,
tf32=None,
tokenization_batch_size=128,
tokenization_mode=online,
tokenized_dataset_cache_dir=/root/dynamic-dpo-v4/tokenized_preferences,
torch_compile=False,
torch_compile_backend=None,
torch_compile_mode=None,
torch_empty_cache_steps=None,
torchdynamo=None,
tp_size=0,
tpu_metrics_debug=False,
tpu_num_cores=None,
trainer_type=new_dpo,
truncation_mode=keep_end,
use_cpu=False,
use_ipex=False,
use_legacy_prediction_loop=False,
use_liger_kernel=False,
use_mps_device=False,
wandb_project=llama3-8b-base-new-method-hh-beta-0.1,
warmup_ratio=0.1,
warmup_steps=0,
weight_decay=0.0,
)
2026-04-21 21:43:42 - INFO - __main__ - Using W&B project from training args: llama3-8b-base-new-method-hh-beta-0.1
2026-04-21 21:43:42 - INFO - __main__ - New-DPO parameters: beta=0.1, q_target=0.45, s_star=0.4, eta=0.1
2026-04-21 21:43:42 - INFO - __main__ - Using persistent HF datasets cache at /root/dynamic-dpo-v4/hf/datasets
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Normalizing raw HH preferences (train): 0%| | 0/43598 [00:00<?, ? examples/s]2026-04-21 21:43:47 - WARNING - __main__ - Dropped 237 non-canonical HH preference examples from split `train` before normalization (126 x HH preprocessing expects exactly one final assistant response in chosen/rejected suffixes., 111 x HH chosen/rejected transcripts must each contain a divergent assistant response.).
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Normalizing raw HH preferences (test): 0%| | 0/2339 [00:00<?, ? examples/s]2026-04-21 21:43:52 - WARNING - __main__ - Dropped 15 non-canonical HH preference examples from split `test` before normalization (9 x HH preprocessing expects exactly one final assistant response in chosen/rejected suffixes., 6 x HH chosen/rejected transcripts must each contain a divergent assistant response.).
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2026-04-21 21:43:52 - INFO - __main__ - Training on the following splits: ['train : 43598', 'test : 2339']
[INFO|tokenization_utils_base.py:2058] 2026-04-21 21:43:52,551 >> loading file tokenizer.json
[INFO|tokenization_utils_base.py:2058] 2026-04-21 21:43:52,551 >> loading file tokenizer.model
[INFO|tokenization_utils_base.py:2058] 2026-04-21 21:43:52,551 >> loading file added_tokens.json
[INFO|tokenization_utils_base.py:2058] 2026-04-21 21:43:52,551 >> loading file special_tokens_map.json
[INFO|tokenization_utils_base.py:2058] 2026-04-21 21:43:52,551 >> loading file tokenizer_config.json
[INFO|tokenization_utils_base.py:2058] 2026-04-21 21:43:52,551 >> loading file chat_template.jinja
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[INFO|tokenization_utils_base.py:2323] 2026-04-21 21:43:52,994 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
/root/dynamic-dpo-v4/scripts/tokenized_dpo_trainer.py:391: UserWarning: You passed a model_id to the trainer. This will automatically create an `AutoModelForCausalLM` or a `PeftModel` (if you passed a `peft_config`) for you.
warnings.warn(
[WARNING|logging.py:328] 2026-04-21 21:43:53,107 >> You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
/root/dynamic-dpo-v4/scripts/tokenized_dpo_trainer.py:391: UserWarning: You passed a model_id to the trainer. This will automatically create an `AutoModelForCausalLM` or a `PeftModel` (if you passed a `peft_config`) for you.
warnings.warn(
Loading checkpoint shards: 0%| | 0/7 [00:00<?, ?it/s][WARNING|logging.py:328] 2026-04-21 21:43:53,147 >> You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
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[WARNING|trainer.py:821] 2026-04-21 21:43:53,191 >> Trainer.tokenizer is now deprecated. You should use `Trainer.processing_class = processing_class` instead.
2026-04-21 21:43:53 - INFO - __main__ - Processed train sample 41905:
Prompt:
<|begin_of_text|><|start_header_id|>user<|end_header_id|>
What is the best way to clean my refrigerator?<|eot_id|><|start_header_id|>assistant<|end_header_id|>
Well, I have a few ideas, but the best way to know what works best is to run some tests and then analyze the data to figure out which technique works best.<|eot_id|><|start_header_id|>user<|end_header_id|>
What are your ideas?<|eot_id|>
Chosen:
<|start_header_id|>assistant<|end_header_id|>
Some of my ideas include wiping down the interior with a rag, using bleach and water to wipe down the door, emptying the contents of the fridge to scrub the shelves with a clean cloth, cleaning the interior of the fridge with vinegar and water, and using a vacuum cleaner to clean the interior.<|eot_id|>
Rejected:
<|start_header_id|>assistant<|end_header_id|>
I was thinking that you could try different types of soap, which could be a variation of “soap,” like antibacterial soap. I was also thinking that you could try using different tools, like a toothbrush, to clean the inside. Or I was thinking that you could try different ways to get the gunk out, like using a squeegee, or using a paper towel. I was also thinking you could try other types of cleaning, like vacuuming, but I think that could have the opposite of the desired effect.<|eot_id|>
Loading checkpoint shards: 0%| | 0/7 [00:00<?, ?it/s]/root/dynamic-dpo-v4/scripts/tokenized_dpo_trainer.py:391: UserWarning: You passed a model_id to the trainer. This will automatically create an `AutoModelForCausalLM` or a `PeftModel` (if you passed a `peft_config`) for you.
warnings.warn(
[INFO|configuration_utils.py:691] 2026-04-21 21:43:53,228 >> loading configuration file /root/dynamic-dpo-v4/sft-checkpoints/llama-3-8b-base-sft-hh-helpful-4xh200/config.json
[INFO|configuration_utils.py:765] 2026-04-21 21:43:53,229 >> Model config LlamaConfig {
"architectures": [
"LlamaForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 128000,
"eos_token_id": 128001,
"head_dim": 128,
"hidden_act": "silu",
"hidden_size": 4096,
"initializer_range": 0.02,
"intermediate_size": 14336,
"max_position_embeddings": 8192,
"mlp_bias": false,
"model_type": "llama",
"num_attention_heads": 32,
"num_hidden_layers": 32,
"num_key_value_heads": 8,
"pretraining_tp": 1,
"rms_norm_eps": 1e-05,
"rope_scaling": null,
"rope_theta": 500000.0,
"tie_word_embeddings": false,
"torch_dtype": "bfloat16",
"transformers_version": "4.51.0",
"use_cache": false,
"vocab_size": 128256
}
Loading checkpoint shards: 100%|██████████| 7/7 [00:00<00:00, 1467.86it/s]
[WARNING|trainer.py:821] 2026-04-21 21:43:53,235 >> Trainer.tokenizer is now deprecated. You should use `Trainer.processing_class = processing_class` instead.
[INFO|modeling_utils.py:1121] 2026-04-21 21:43:53,238 >> loading weights file /root/dynamic-dpo-v4/sft-checkpoints/llama-3-8b-base-sft-hh-helpful-4xh200/model.safetensors.index.json
[INFO|modeling_utils.py:2167] 2026-04-21 21:43:53,238 >> Instantiating LlamaForCausalLM model under default dtype torch.bfloat16.
[WARNING|logging.py:328] 2026-04-21 21:43:53,239 >> You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
[INFO|configuration_utils.py:1142] 2026-04-21 21:43:53,241 >> Generate config GenerationConfig {
"bos_token_id": 128000,
"eos_token_id": 128001,
"use_cache": false
}
Loading checkpoint shards: 0%| | 0/7 [00:00<?, ?it/s]/root/dynamic-dpo-v4/scripts/tokenized_dpo_trainer.py:391: UserWarning: You passed a model_id to the trainer. This will automatically create an `AutoModelForCausalLM` or a `PeftModel` (if you passed a `peft_config`) for you.
warnings.warn(
[WARNING|logging.py:328] 2026-04-21 21:43:53,318 >> You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
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[WARNING|trainer.py:821] 2026-04-21 21:43:53,403 >> Trainer.tokenizer is now deprecated. You should use `Trainer.processing_class = processing_class` instead.
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[INFO|modeling_utils.py:4926] 2026-04-21 21:44:04,766 >> All model checkpoint weights were used when initializing LlamaForCausalLM.
[INFO|modeling_utils.py:4934] 2026-04-21 21:44:04,766 >> All the weights of LlamaForCausalLM were initialized from the model checkpoint at /root/dynamic-dpo-v4/sft-checkpoints/llama-3-8b-base-sft-hh-helpful-4xh200.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlamaForCausalLM for predictions without further training.
[INFO|configuration_utils.py:1095] 2026-04-21 21:44:04,768 >> loading configuration file /root/dynamic-dpo-v4/sft-checkpoints/llama-3-8b-base-sft-hh-helpful-4xh200/generation_config.json
[INFO|configuration_utils.py:1142] 2026-04-21 21:44:04,769 >> Generate config GenerationConfig {
"bos_token_id": 128000,
"do_sample": true,
"eos_token_id": 128001,
"max_length": 4096,
"temperature": 0.6,
"top_p": 0.9
}
[INFO|configuration_utils.py:691] 2026-04-21 21:44:04,769 >> loading configuration file /root/dynamic-dpo-v4/sft-checkpoints/llama-3-8b-base-sft-hh-helpful-4xh200/config.json
[INFO|configuration_utils.py:765] 2026-04-21 21:44:04,770 >> Model config LlamaConfig {
"architectures": [
"LlamaForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 128000,
"eos_token_id": 128001,
"head_dim": 128,
"hidden_act": "silu",
"hidden_size": 4096,
"initializer_range": 0.02,
"intermediate_size": 14336,
"max_position_embeddings": 8192,
"mlp_bias": false,
"model_type": "llama",
"num_attention_heads": 32,
"num_hidden_layers": 32,
"num_key_value_heads": 8,
"pretraining_tp": 1,
"rms_norm_eps": 1e-05,
"rope_scaling": null,
"rope_theta": 500000.0,
"tie_word_embeddings": false,
"torch_dtype": "bfloat16",
"transformers_version": "4.51.0",
"use_cache": false,
"vocab_size": 128256
}
[INFO|modeling_utils.py:1121] 2026-04-21 21:44:04,771 >> loading weights file /root/dynamic-dpo-v4/sft-checkpoints/llama-3-8b-base-sft-hh-helpful-4xh200/model.safetensors.index.json
[INFO|modeling_utils.py:2167] 2026-04-21 21:44:04,771 >> Instantiating LlamaForCausalLM model under default dtype torch.bfloat16.
[INFO|configuration_utils.py:1142] 2026-04-21 21:44:04,773 >> Generate config GenerationConfig {
"bos_token_id": 128000,
"eos_token_id": 128001,
"use_cache": false
}
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[INFO|modeling_utils.py:4926] 2026-04-21 21:44:15,821 >> All model checkpoint weights were used when initializing LlamaForCausalLM.
[INFO|modeling_utils.py:4934] 2026-04-21 21:44:15,821 >> All the weights of LlamaForCausalLM were initialized from the model checkpoint at /root/dynamic-dpo-v4/sft-checkpoints/llama-3-8b-base-sft-hh-helpful-4xh200.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlamaForCausalLM for predictions without further training.
[INFO|configuration_utils.py:1095] 2026-04-21 21:44:15,824 >> loading configuration file /root/dynamic-dpo-v4/sft-checkpoints/llama-3-8b-base-sft-hh-helpful-4xh200/generation_config.json
[INFO|configuration_utils.py:1142] 2026-04-21 21:44:15,824 >> Generate config GenerationConfig {
"bos_token_id": 128000,
"do_sample": true,
"eos_token_id": 128001,
"max_length": 4096,
"temperature": 0.6,
"top_p": 0.9
}
[WARNING|trainer.py:821] 2026-04-21 21:44:15,826 >> Trainer.tokenizer is now deprecated. You should use `Trainer.processing_class = processing_class` instead.
[WARNING|trainer.py:816] 2026-04-21 21:44:15,826 >> Trainer.tokenizer is now deprecated. You should use Trainer.processing_class instead.
[WARNING|trainer.py:816] 2026-04-21 21:44:15,835 >> Trainer.tokenizer is now deprecated. You should use Trainer.processing_class instead.
[WARNING|trainer.py:816] 2026-04-21 21:44:15,836 >> Trainer.tokenizer is now deprecated. You should use Trainer.processing_class instead.
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[WARNING|trainer.py:816] 2026-04-21 21:54:41,186 >> Trainer.tokenizer is now deprecated. You should use Trainer.processing_class instead.
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[WARNING|trainer.py:816] 2026-04-21 21:54:42,677 >> Trainer.tokenizer is now deprecated. You should use Trainer.processing_class instead.
/root/dynamic-dpo-v4/scripts/tokenized_dpo_trainer.py:518: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `NewDPOTrainer.__init__`. Use `processing_class` instead.
super().__init__(
[WARNING|trainer.py:816] 2026-04-21 21:54:42,677 >> Trainer.tokenizer is now deprecated. You should use Trainer.processing_class instead.
[WARNING|trainer.py:816] 2026-04-21 21:54:42,678 >> Trainer.tokenizer is now deprecated. You should use Trainer.processing_class instead.
[WARNING|trainer.py:816] 2026-04-21 21:54:42,694 >> Trainer.tokenizer is now deprecated. You should use Trainer.processing_class instead.
[WARNING|trainer.py:816] 2026-04-21 21:54:42,694 >> Trainer.tokenizer is now deprecated. You should use Trainer.processing_class instead.
[WARNING|trainer.py:816] 2026-04-21 21:54:42,698 >> Trainer.tokenizer is now deprecated. You should use Trainer.processing_class instead.
[WARNING|trainer.py:816] 2026-04-21 21:54:42,698 >> Trainer.tokenizer is now deprecated. You should use Trainer.processing_class instead.
[WARNING|trainer.py:816] 2026-04-21 21:54:42,699 >> Trainer.tokenizer is now deprecated. You should use Trainer.processing_class instead.
[WARNING|trainer.py:816] 2026-04-21 21:54:42,699 >> Trainer.tokenizer is now deprecated. You should use Trainer.processing_class instead.
[WARNING|trainer.py:816] 2026-04-21 21:54:42,706 >> Trainer.tokenizer is now deprecated. You should use Trainer.processing_class instead.
/root/dynamic-dpo-v4/scripts/tokenized_dpo_trainer.py:518: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `NewDPOTrainer.__init__`. Use `processing_class` instead.
super().__init__(
[WARNING|trainer.py:816] 2026-04-21 21:54:42,710 >> Trainer.tokenizer is now deprecated. You should use Trainer.processing_class instead.
/root/dynamic-dpo-v4/scripts/tokenized_dpo_trainer.py:518: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `NewDPOTrainer.__init__`. Use `processing_class` instead.
super().__init__(
[WARNING|trainer.py:816] 2026-04-21 21:54:42,711 >> Trainer.tokenizer is now deprecated. You should use Trainer.processing_class instead.
/root/dynamic-dpo-v4/scripts/tokenized_dpo_trainer.py:518: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `NewDPOTrainer.__init__`. Use `processing_class` instead.
super().__init__(
[INFO|trainer.py:748] 2026-04-21 21:54:47,582 >> Using auto half precision backend
/root/dynamic-dpo-v4/.venv/lib/python3.11/site-packages/accelerate/accelerator.py:1557: UserWarning: Upcasted low precision parameters in LlamaForCausalLM because mixed precision turned on in FSDP. Affects: model.embed_tokens.weight, model.norm.weight, lm_head.weight.
warnings.warn(
/root/dynamic-dpo-v4/.venv/lib/python3.11/site-packages/accelerate/accelerator.py:1557: UserWarning: Upcasted low precision parameters in LlamaDecoderLayer because mixed precision turned on in FSDP. Affects: self_attn.q_proj.weight, self_attn.k_proj.weight, self_attn.v_proj.weight, self_attn.o_proj.weight, mlp.gate_proj.weight, mlp.up_proj.weight, mlp.down_proj.weight, input_layernorm.weight, post_attention_layernorm.weight.
warnings.warn(
/root/dynamic-dpo-v4/.venv/lib/python3.11/site-packages/accelerate/accelerator.py:1563: UserWarning: FSDP upcast of low precision parameters may affect the precision of model checkpoints.
warnings.warn(
[INFO|trainer.py:2414] 2026-04-21 21:54:56,469 >> ***** Running training *****
[INFO|trainer.py:2415] 2026-04-21 21:54:56,469 >> Num examples = 43,598
[INFO|trainer.py:2416] 2026-04-21 21:54:56,469 >> Num Epochs = 1
[INFO|trainer.py:2417] 2026-04-21 21:54:56,469 >> Instantaneous batch size per device = 8
[INFO|trainer.py:2420] 2026-04-21 21:54:56,469 >> Total train batch size (w. parallel, distributed & accumulation) = 64
[INFO|trainer.py:2421] 2026-04-21 21:54:56,469 >> Gradient Accumulation steps = 2
[INFO|trainer.py:2422] 2026-04-21 21:54:56,469 >> Total optimization steps = 681
[INFO|trainer.py:2423] 2026-04-21 21:54:56,470 >> Number of trainable parameters = 2,007,565,312
[INFO|integration_utils.py:831] 2026-04-21 21:54:56,471 >> Automatic Weights & Biases logging enabled, to disable set os.environ["WANDB_DISABLED"] = "true"
wandb: Currently logged in as: feng-cheng (feng-cheng-northeastern-university). Use `wandb login --relogin` to force relogin
wandb: - Waiting for wandb.init()...
wandb: \ Waiting for wandb.init()...
wandb: | Waiting for wandb.init()...
wandb: / Waiting for wandb.init()...
wandb: - Waiting for wandb.init()...
wandb: \ Waiting for wandb.init()...
wandb: wandb version 0.26.0 is available! To upgrade, please run:
wandb: $ pip install wandb --upgrade
wandb: Tracking run with wandb version 0.17.5
wandb: Run data is saved locally in /root/dynamic-dpo-v4/wandb/wandb/run-20260421_215457-yuvsexn3
wandb: Run `wandb offline` to turn off syncing.
wandb: Syncing run llama-3-8b-base-new-dpo-hh-helpful-s_star0.4-4xh200-batch-64-20260421-214335-rerun
wandb: ⭐️ View project at https://wandb.ai/feng-cheng-northeastern-university/llama3-8b-base-new-method-hh-beta-0.1
wandb: 🚀 View run at https://wandb.ai/feng-cheng-northeastern-university/llama3-8b-base-new-method-hh-beta-0.1/runs/yuvsexn3
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[WARNING|modeling_utils.py:1713] 2026-04-21 21:55:04,936 >> Could not estimate the number of tokens of the input, floating-point operations will not be computed
[WARNING|modeling_utils.py:1713] 2026-04-21 21:55:04,938 >> Could not estimate the number of tokens of the input, floating-point operations will not be computed
[WARNING|modeling_utils.py:1713] 2026-04-21 21:55:04,946 >> Could not estimate the number of tokens of the input, floating-point operations will not be computed
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{'loss': 1.389, 'grad_norm': 83.51022338867188, 'learning_rate': 0.0, 'fcm_dpo/beta': 0.10000000149011612, 'fcm_dpo/q_t': 0.5005706548690796, 'fcm_dpo/delta': 0.0, 'fcm_dpo/margin': -0.02287006378173828, 'margin_dpo/margin_mean': -0.02287048101425171, 'margin_dpo/margin_std': 0.41920793056488037, 'logps/chosen': -50.1435661315918, 'logps/rejected': -74.09991455078125, 'logps/ref_chosen': -50.14883804321289, 'logps/ref_rejected': -74.1280517578125, 'logits/chosen': -0.4974287748336792, 'logits/rejected': -0.43299180269241333, 'epoch': 0.0}
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{'loss': 1.3874, 'grad_norm': 89.51734924316406, 'learning_rate': 2.898550724637681e-08, 'fcm_dpo/beta': 0.10000000894069672, 'fcm_dpo/q_t': 0.500194251537323, 'fcm_dpo/delta': 0.0, 'fcm_dpo/margin': -0.007774516940116882, 'margin_dpo/margin_mean': -0.007774434983730316, 'margin_dpo/margin_std': 0.37205374240875244, 'logps/chosen': -56.05889892578125, 'logps/rejected': -78.68702697753906, 'logps/ref_chosen': -56.05734634399414, 'logps/ref_rejected': -78.69325256347656, 'logits/chosen': -0.4900396764278412, 'logits/rejected': -0.4533483386039734, 'epoch': 0.01}
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{'loss': 1.3849, 'grad_norm': 70.37712097167969, 'learning_rate': 6.521739130434782e-08, 'fcm_dpo/beta': 0.10000000894069672, 'fcm_dpo/q_t': 0.49955543875694275, 'fcm_dpo/delta': 0.0, 'fcm_dpo/margin': 0.017793914303183556, 'margin_dpo/margin_mean': 0.017794013023376465, 'margin_dpo/margin_std': 0.40502458810806274, 'logps/chosen': -59.53853225708008, 'logps/rejected': -91.18217468261719, 'logps/ref_chosen': -59.54457473754883, 'logps/ref_rejected': -91.17041778564453, 'logits/chosen': -0.49457064270973206, 'logits/rejected': -0.4558273255825043, 'epoch': 0.01}
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{'loss': 1.3854, 'grad_norm': 64.22943878173828, 'learning_rate': 1.0144927536231885e-07, 'fcm_dpo/beta': 0.10000000894069672, 'fcm_dpo/q_t': 0.4996658265590668, 'fcm_dpo/delta': 0.0, 'fcm_dpo/margin': 0.013358664698898792, 'margin_dpo/margin_mean': 0.01335877738893032, 'margin_dpo/margin_std': 0.3935544788837433, 'logps/chosen': -58.85475540161133, 'logps/rejected': -92.97565460205078, 'logps/ref_chosen': -58.83195877075195, 'logps/ref_rejected': -92.93949890136719, 'logits/chosen': -0.48777151107788086, 'logits/rejected': -0.4582846164703369, 'epoch': 0.02}
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{'loss': 1.3775, 'grad_norm': 73.8072509765625, 'learning_rate': 1.3768115942028986e-07, 'fcm_dpo/beta': 0.10000000894069672, 'fcm_dpo/q_t': 0.49772581458091736, 'fcm_dpo/delta': 0.0, 'fcm_dpo/margin': 0.09099045395851135, 'margin_dpo/margin_mean': 0.09099055081605911, 'margin_dpo/margin_std': 0.35805386304855347, 'logps/chosen': -59.618431091308594, 'logps/rejected': -82.83003234863281, 'logps/ref_chosen': -59.6396598815918, 'logps/ref_rejected': -82.76026916503906, 'logits/chosen': -0.5034265518188477, 'logits/rejected': -0.45439839363098145, 'epoch': 0.03}
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{'loss': 1.3652, 'grad_norm': 73.70997619628906, 'learning_rate': 1.7391304347826085e-07, 'fcm_dpo/beta': 0.10000000894069672, 'fcm_dpo/q_t': 0.49459710717201233, 'fcm_dpo/delta': 0.0, 'fcm_dpo/margin': 0.21624115109443665, 'margin_dpo/margin_mean': 0.21624140441417694, 'margin_dpo/margin_std': 0.4134984016418457, 'logps/chosen': -53.1678352355957, 'logps/rejected': -89.17488098144531, 'logps/ref_chosen': -53.205284118652344, 'logps/ref_rejected': -88.99608612060547, 'logits/chosen': -0.5030972361564636, 'logits/rejected': -0.47600775957107544, 'epoch': 0.04}
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{'loss': 1.3399, 'grad_norm': 87.57738494873047, 'learning_rate': 2.1014492753623187e-07, 'fcm_dpo/beta': 0.10000000894069672, 'fcm_dpo/q_t': 0.4880555272102356, 'fcm_dpo/delta': 0.0, 'fcm_dpo/margin': 0.4783309996128082, 'margin_dpo/margin_mean': 0.47833117842674255, 'margin_dpo/margin_std': 0.5532158017158508, 'logps/chosen': -53.46284103393555, 'logps/rejected': -98.26229858398438, 'logps/ref_chosen': -53.5526008605957, 'logps/ref_rejected': -97.87371826171875, 'logits/chosen': -0.5126634240150452, 'logits/rejected': -0.4724017083644867, 'epoch': 0.04}
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{'loss': 1.3121, 'grad_norm': 82.80741119384766, 'learning_rate': 2.463768115942029e-07, 'fcm_dpo/beta': 0.10000000894069672, 'fcm_dpo/q_t': 0.48065242171287537, 'fcm_dpo/delta': 0.0, 'fcm_dpo/margin': 0.7770208120346069, 'margin_dpo/margin_mean': 0.7770206332206726, 'margin_dpo/margin_std': 0.8431359529495239, 'logps/chosen': -56.210533142089844, 'logps/rejected': -92.4262924194336, 'logps/ref_chosen': -56.3298454284668, 'logps/ref_rejected': -91.76858520507812, 'logits/chosen': -0.5122802257537842, 'logits/rejected': -0.4792337417602539, 'epoch': 0.05}
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{'loss': 1.2605, 'grad_norm': 60.205745697021484, 'learning_rate': 2.8260869565217386e-07, 'fcm_dpo/beta': 0.10000000894069672, 'fcm_dpo/q_t': 0.46629637479782104, 'fcm_dpo/delta': 0.0, 'fcm_dpo/margin': 1.3613355159759521, 'margin_dpo/margin_mean': 1.3613355159759521, 'margin_dpo/margin_std': 1.4631270170211792, 'logps/chosen': -54.278953552246094, 'logps/rejected': -84.19891357421875, 'logps/ref_chosen': -54.38492965698242, 'logps/ref_rejected': -82.94353485107422, 'logits/chosen': -0.5219647884368896, 'logits/rejected': -0.4850676953792572, 'epoch': 0.06}
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{'loss': 1.1601, 'grad_norm': 68.1404800415039, 'learning_rate': 3.188405797101449e-07, 'fcm_dpo/beta': 0.10669933259487152, 'fcm_dpo/q_t': 0.4380177855491638, 'fcm_dpo/delta': 0.12330988794565201, 'fcm_dpo/margin': 2.4058146476745605, 'margin_dpo/margin_mean': 2.4058141708374023, 'margin_dpo/margin_std': 2.224526882171631, 'logps/chosen': -54.63410186767578, 'logps/rejected': -100.20404052734375, 'logps/ref_chosen': -54.862335205078125, 'logps/ref_rejected': -98.0264663696289, 'logits/chosen': -0.5121681094169617, 'logits/rejected': -0.4841387867927551, 'epoch': 0.07}
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{'loss': 1.0694, 'grad_norm': 68.53203582763672, 'learning_rate': 3.5507246376811595e-07, 'fcm_dpo/beta': 0.11535553634166718, 'fcm_dpo/q_t': 0.4073707163333893, 'fcm_dpo/delta': 0.0067912861704826355, 'fcm_dpo/margin': 3.4076931476593018, 'margin_dpo/margin_mean': 3.4076931476593018, 'margin_dpo/margin_std': 3.365309953689575, 'logps/chosen': -58.12030029296875, 'logps/rejected': -94.91819763183594, 'logps/ref_chosen': -58.304595947265625, 'logps/ref_rejected': -91.69480895996094, 'logits/chosen': -0.562477707862854, 'logits/rejected': -0.5116110444068909, 'epoch': 0.07}
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{'loss': 0.968, 'grad_norm': 52.22880935668945, 'learning_rate': 3.9130434782608694e-07, 'fcm_dpo/beta': 0.10359964519739151, 'fcm_dpo/q_t': 0.3696584403514862, 'fcm_dpo/delta': -0.19395628571510315, 'fcm_dpo/margin': 5.653986930847168, 'margin_dpo/margin_mean': 5.653987407684326, 'margin_dpo/margin_std': 5.778587818145752, 'logps/chosen': -56.34511184692383, 'logps/rejected': -91.62686157226562, 'logps/ref_chosen': -56.06591796875, 'logps/ref_rejected': -85.69367980957031, 'logits/chosen': -0.5961982011795044, 'logits/rejected': -0.5513918399810791, 'epoch': 0.08}
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{'loss': 0.9663, 'grad_norm': 53.557796478271484, 'learning_rate': 4.2753623188405794e-07, 'fcm_dpo/beta': 0.08351375162601471, 'fcm_dpo/q_t': 0.3656514883041382, 'fcm_dpo/delta': -0.2116357386112213, 'fcm_dpo/margin': 7.191043853759766, 'margin_dpo/margin_mean': 7.191043853759766, 'margin_dpo/margin_std': 7.640544891357422, 'logps/chosen': -62.0140266418457, 'logps/rejected': -98.24510192871094, 'logps/ref_chosen': -60.6871337890625, 'logps/ref_rejected': -89.72715759277344, 'logits/chosen': -0.614372193813324, 'logits/rejected': -0.5657563209533691, 'epoch': 0.09}
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{'loss': 0.9904, 'grad_norm': 41.2183723449707, 'learning_rate': 4.63768115942029e-07, 'fcm_dpo/beta': 0.06861739605665207, 'fcm_dpo/q_t': 0.37094324827194214, 'fcm_dpo/delta': -0.19986796379089355, 'fcm_dpo/margin': 8.604007720947266, 'margin_dpo/margin_mean': 8.604008674621582, 'margin_dpo/margin_std': 10.206991195678711, 'logps/chosen': -63.8182487487793, 'logps/rejected': -103.9700927734375, 'logps/ref_chosen': -61.75325393676758, 'logps/ref_rejected': -93.30108642578125, 'logits/chosen': -0.6187667846679688, 'logits/rejected': -0.5872984528541565, 'epoch': 0.1}
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{'loss': 0.98, 'grad_norm': 39.173946380615234, 'learning_rate': 5e-07, 'fcm_dpo/beta': 0.05661847069859505, 'fcm_dpo/q_t': 0.3718249201774597, 'fcm_dpo/delta': -0.1891469657421112, 'fcm_dpo/margin': 10.259188652038574, 'margin_dpo/margin_mean': 10.259187698364258, 'margin_dpo/margin_std': 11.377448081970215, 'logps/chosen': -63.28239059448242, 'logps/rejected': -98.00967407226562, 'logps/ref_chosen': -59.548004150390625, 'logps/ref_rejected': -84.01609802246094, 'logits/chosen': -0.6201697587966919, 'logits/rejected': -0.5813671350479126, 'epoch': 0.1}
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{'loss': 0.9415, 'grad_norm': 31.45458221435547, 'learning_rate': 4.999176576834721e-07, 'fcm_dpo/beta': 0.04313134402036667, 'fcm_dpo/q_t': 0.34925174713134766, 'fcm_dpo/delta': -0.354682594537735, 'fcm_dpo/margin': 17.1324405670166, 'margin_dpo/margin_mean': 17.132436752319336, 'margin_dpo/margin_std': 21.05853843688965, 'logps/chosen': -67.56647491455078, 'logps/rejected': -122.8857421875, 'logps/ref_chosen': -59.86931228637695, 'logps/ref_rejected': -98.05613708496094, 'logits/chosen': -0.6573521494865417, 'logits/rejected': -0.6307379603385925, 'epoch': 0.11}
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{'loss': 0.9939, 'grad_norm': 28.407453536987305, 'learning_rate': 4.996706849759452e-07, 'fcm_dpo/beta': 0.03168341889977455, 'fcm_dpo/q_t': 0.3687431514263153, 'fcm_dpo/delta': -0.22349825501441956, 'fcm_dpo/margin': 19.243648529052734, 'margin_dpo/margin_mean': 19.243648529052734, 'margin_dpo/margin_std': 23.982927322387695, 'logps/chosen': -66.81375122070312, 'logps/rejected': -116.2920913696289, 'logps/ref_chosen': -56.18925857543945, 'logps/ref_rejected': -86.42393493652344, 'logits/chosen': -0.6761894822120667, 'logits/rejected': -0.6410226821899414, 'epoch': 0.12}
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{'loss': 1.0959, 'grad_norm': 29.300512313842773, 'learning_rate': 4.645557588393406e-07, 'fcm_dpo/beta': 0.0053649842739105225, 'fcm_dpo/q_t': 0.40541133284568787, 'fcm_dpo/delta': -0.02835622988641262, 'fcm_dpo/margin': 79.64360809326172, 'margin_dpo/margin_mean': 79.64360046386719, 'margin_dpo/margin_std': 116.92179107666016, 'logps/chosen': -156.86700439453125, 'logps/rejected': -266.4975891113281, 'logps/ref_chosen': -62.996971130371094, 'logps/ref_rejected': -92.98394012451172, 'logits/chosen': -0.3354695737361908, 'logits/rejected': -0.3250008523464203, 'epoch': 0.26}
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{'loss': 1.0541, 'grad_norm': 18.73993492126465, 'learning_rate': 4.611919330113591e-07, 'fcm_dpo/beta': 0.004915366414934397, 'fcm_dpo/q_t': 0.39298662543296814, 'fcm_dpo/delta': -0.08844007551670074, 'fcm_dpo/margin': 98.45795440673828, 'margin_dpo/margin_mean': 98.45795440673828, 'margin_dpo/margin_std': 131.67587280273438, 'logps/chosen': -155.4091796875, 'logps/rejected': -293.9116516113281, 'logps/ref_chosen': -57.0670280456543, 'logps/ref_rejected': -97.1115493774414, 'logits/chosen': -0.2953912019729614, 'logits/rejected': -0.29680582880973816, 'epoch': 0.26}
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{'loss': 1.1531, 'grad_norm': 19.846059799194336, 'learning_rate': 4.5768898691940836e-07, 'fcm_dpo/beta': 0.00469121104106307, 'fcm_dpo/q_t': 0.423015296459198, 'fcm_dpo/delta': -0.007265460677444935, 'fcm_dpo/margin': 72.3204574584961, 'margin_dpo/margin_mean': 72.3204574584961, 'margin_dpo/margin_std': 118.7593994140625, 'logps/chosen': -150.46461486816406, 'logps/rejected': -243.45437622070312, 'logps/ref_chosen': -54.840736389160156, 'logps/ref_rejected': -75.51002502441406, 'logits/chosen': -0.3211399018764496, 'logits/rejected': -0.31003421545028687, 'epoch': 0.27}
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{'loss': 1.0829, 'grad_norm': 18.63943862915039, 'learning_rate': 4.5404922808905543e-07, 'fcm_dpo/beta': 0.004630076698958874, 'fcm_dpo/q_t': 0.4038674235343933, 'fcm_dpo/delta': -0.02935381792485714, 'fcm_dpo/margin': 92.37378692626953, 'margin_dpo/margin_mean': 92.37378692626953, 'margin_dpo/margin_std': 125.8380126953125, 'logps/chosen': -155.59190368652344, 'logps/rejected': -277.10418701171875, 'logps/ref_chosen': -57.72148895263672, 'logps/ref_rejected': -86.85997009277344, 'logits/chosen': -0.3224960267543793, 'logits/rejected': -0.31152957677841187, 'epoch': 0.28}
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{'loss': 1.0971, 'grad_norm': 19.838130950927734, 'learning_rate': 4.5027505416968985e-07, 'fcm_dpo/beta': 0.004372724797576666, 'fcm_dpo/q_t': 0.4060741066932678, 'fcm_dpo/delta': -0.041835661977529526, 'fcm_dpo/margin': 94.63658142089844, 'margin_dpo/margin_mean': 94.63658142089844, 'margin_dpo/margin_std': 133.46847534179688, 'logps/chosen': -171.98052978515625, 'logps/rejected': -297.82037353515625, 'logps/ref_chosen': -58.26164627075195, 'logps/ref_rejected': -89.46485900878906, 'logits/chosen': -0.2853700518608093, 'logits/rejected': -0.2791460156440735, 'epoch': 0.29}
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{'loss': 1.0801, 'grad_norm': 21.282487869262695, 'learning_rate': 4.4636895135509966e-07, 'fcm_dpo/beta': 0.0042917924001812935, 'fcm_dpo/q_t': 0.40244197845458984, 'fcm_dpo/delta': -0.03731077164411545, 'fcm_dpo/margin': 101.45069122314453, 'margin_dpo/margin_mean': 101.45067596435547, 'margin_dpo/margin_std': 138.32688903808594, 'logps/chosen': -161.27999877929688, 'logps/rejected': -290.16351318359375, 'logps/ref_chosen': -55.71953201293945, 'logps/ref_rejected': -83.15235137939453, 'logits/chosen': -0.29983407258987427, 'logits/rejected': -0.2885088324546814, 'epoch': 0.29}
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***** Running Evaluation *****
[INFO|trainer.py:4309] 2026-04-21 22:03:32,118 >> Num examples = 2339
[INFO|trainer.py:4312] 2026-04-21 22:03:32,118 >> Batch size = 8
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{'eval_loss': 0.6239348649978638, 'eval_runtime': 39.6889, 'eval_samples_per_second': 58.933, 'eval_steps_per_second': 1.864, 'eval_fcm_dpo/beta': 0.004899847786873579, 'eval_fcm_dpo/q_t': 0.4392388164997101, 'eval_fcm_dpo/delta': 0.03208634629845619, 'eval_fcm_dpo/margin': 58.008628845214844, 'eval_margin_dpo/margin_mean': 58.008628845214844, 'eval_margin_dpo/margin_std': 147.6545867919922, 'eval_logps/chosen': -225.8389892578125, 'eval_logps/rejected': -291.5945129394531, 'eval_logps/ref_chosen': -79.05104064941406, 'eval_logps/ref_rejected': -86.79793548583984, 'eval_logits/chosen': -0.3472006916999817, 'eval_logits/rejected': -0.3329962491989136, 'epoch': 0.29}
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{'loss': 1.0848, 'grad_norm': 24.034622192382812, 'learning_rate': 4.4233349274571974e-07, 'fcm_dpo/beta': 0.005112385377287865, 'fcm_dpo/q_t': 0.39707884192466736, 'fcm_dpo/delta': -0.07373825460672379, 'fcm_dpo/margin': 91.88821411132812, 'margin_dpo/margin_mean': 91.88821411132812, 'margin_dpo/margin_std': 137.34268188476562, 'logps/chosen': -181.0006103515625, 'logps/rejected': -299.8582763671875, 'logps/ref_chosen': -65.13258361816406, 'logps/ref_rejected': -92.10203552246094, 'logits/chosen': -0.3471163213253021, 'logits/rejected': -0.3326929211616516, 'epoch': 0.3}
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{'loss': 1.0332, 'grad_norm': 25.71703338623047, 'learning_rate': 4.381713366536311e-07, 'fcm_dpo/beta': 0.00456308713182807, 'fcm_dpo/q_t': 0.3846554160118103, 'fcm_dpo/delta': -0.12305764853954315, 'fcm_dpo/margin': 112.89747619628906, 'margin_dpo/margin_mean': 112.89747619628906, 'margin_dpo/margin_std': 143.22720336914062, 'logps/chosen': -175.38168334960938, 'logps/rejected': -320.81304931640625, 'logps/ref_chosen': -54.52837371826172, 'logps/ref_rejected': -87.06227111816406, 'logits/chosen': -0.30507659912109375, 'logits/rejected': -0.2925286889076233, 'epoch': 0.31}
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{'loss': 1.0502, 'grad_norm': 27.700122833251953, 'learning_rate': 4.3388522485142885e-07, 'fcm_dpo/beta': 0.004155799280852079, 'fcm_dpo/q_t': 0.39112934470176697, 'fcm_dpo/delta': -0.09338673204183578, 'fcm_dpo/margin': 117.60514068603516, 'margin_dpo/margin_mean': 117.60514068603516, 'margin_dpo/margin_std': 151.13796997070312, 'logps/chosen': -197.89137268066406, 'logps/rejected': -345.84637451171875, 'logps/ref_chosen': -59.905250549316406, 'logps/ref_rejected': -90.25511932373047, 'logits/chosen': -0.2812441289424896, 'logits/rejected': -0.265227735042572, 'epoch': 0.32}
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{'loss': 1.0982, 'grad_norm': 27.14980697631836, 'learning_rate': 4.2947798076611047e-07, 'fcm_dpo/beta': 0.0038633563090115786, 'fcm_dpo/q_t': 0.406075656414032, 'fcm_dpo/delta': -0.0188637413084507, 'fcm_dpo/margin': 107.99397277832031, 'margin_dpo/margin_mean': 107.99397277832031, 'margin_dpo/margin_std': 155.56427001953125, 'logps/chosen': -209.11544799804688, 'logps/rejected': -347.15234375, 'logps/ref_chosen': -57.68498611450195, 'logps/ref_rejected': -87.72792053222656, 'logits/chosen': -0.2910076379776001, 'logits/rejected': -0.27931129932403564, 'epoch': 0.32}
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{'loss': 1.0374, 'grad_norm': 21.774181365966797, 'learning_rate': 4.249525076191759e-07, 'fcm_dpo/beta': 0.003635880770161748, 'fcm_dpo/q_t': 0.3866313397884369, 'fcm_dpo/delta': -0.11107522249221802, 'fcm_dpo/margin': 138.54534912109375, 'margin_dpo/margin_mean': 138.5453643798828, 'margin_dpo/margin_std': 173.9648895263672, 'logps/chosen': -216.45687866210938, 'logps/rejected': -393.79248046875, 'logps/ref_chosen': -54.47245407104492, 'logps/ref_rejected': -93.26266479492188, 'logits/chosen': -0.26980072259902954, 'logits/rejected': -0.2639961540699005, 'epoch': 0.33}
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{'loss': 1.0656, 'grad_norm': 29.499502182006836, 'learning_rate': 4.203117865141635e-07, 'fcm_dpo/beta': 0.003416923340409994, 'fcm_dpo/q_t': 0.3975502550601959, 'fcm_dpo/delta': -0.05279744789004326, 'fcm_dpo/margin': 131.7572021484375, 'margin_dpo/margin_mean': 131.7572021484375, 'margin_dpo/margin_std': 169.88063049316406, 'logps/chosen': -219.03005981445312, 'logps/rejected': -379.87677001953125, 'logps/ref_chosen': -58.7701301574707, 'logps/ref_rejected': -87.85963439941406, 'logits/chosen': -0.3394869565963745, 'logits/rejected': -0.31970351934432983, 'epoch': 0.34}
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{'loss': 1.0923, 'grad_norm': 27.207300186157227, 'learning_rate': 3.147047612756302e-07, 'fcm_dpo/beta': 0.002015223726630211, 'fcm_dpo/q_t': 0.4082733690738678, 'fcm_dpo/delta': 0.0017573073273524642, 'fcm_dpo/margin': 197.41522216796875, 'margin_dpo/margin_mean': 197.41522216796875, 'margin_dpo/margin_std': 251.11337280273438, 'logps/chosen': -381.36676025390625, 'logps/rejected': -604.3004760742188, 'logps/ref_chosen': -58.28468704223633, 'logps/ref_rejected': -83.80326843261719, 'logits/chosen': -0.4213026165962219, 'logits/rejected': -0.4106159210205078, 'epoch': 0.48}
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{'loss': 1.0667, 'grad_norm': 28.69426727294922, 'learning_rate': 3.084861204504122e-07, 'fcm_dpo/beta': 0.002033454831689596, 'fcm_dpo/q_t': 0.40213847160339355, 'fcm_dpo/delta': -0.02132582850754261, 'fcm_dpo/margin': 206.72314453125, 'margin_dpo/margin_mean': 206.72314453125, 'margin_dpo/margin_std': 237.6807403564453, 'logps/chosen': -349.00677490234375, 'logps/rejected': -587.0137939453125, 'logps/ref_chosen': -62.75822067260742, 'logps/ref_rejected': -94.04203033447266, 'logits/chosen': -0.42850977182388306, 'logits/rejected': -0.42162972688674927, 'epoch': 0.48}
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{'loss': 1.1035, 'grad_norm': 32.573978424072266, 'learning_rate': 3.022289525640531e-07, 'fcm_dpo/beta': 0.0019993516616523266, 'fcm_dpo/q_t': 0.41195163130760193, 'fcm_dpo/delta': 0.017332084476947784, 'fcm_dpo/margin': 191.62435913085938, 'margin_dpo/margin_mean': 191.62435913085938, 'margin_dpo/margin_std': 254.1148223876953, 'logps/chosen': -367.4043273925781, 'logps/rejected': -589.1280517578125, 'logps/ref_chosen': -58.59650421142578, 'logps/ref_rejected': -88.69586944580078, 'logits/chosen': -0.46553975343704224, 'logits/rejected': -0.454815149307251, 'epoch': 0.49}
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{'loss': 1.0561, 'grad_norm': 28.016321182250977, 'learning_rate': 2.959373794541426e-07, 'fcm_dpo/beta': 0.001957540400326252, 'fcm_dpo/q_t': 0.3968558609485626, 'fcm_dpo/delta': -0.052527785301208496, 'fcm_dpo/margin': 229.53335571289062, 'margin_dpo/margin_mean': 229.53335571289062, 'margin_dpo/margin_std': 272.4295959472656, 'logps/chosen': -372.17889404296875, 'logps/rejected': -637.9742431640625, 'logps/ref_chosen': -58.18162155151367, 'logps/ref_rejected': -94.44358825683594, 'logits/chosen': -0.45491886138916016, 'logits/rejected': -0.44332224130630493, 'epoch': 0.5}
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{'loss': 1.0594, 'grad_norm': 25.25508689880371, 'learning_rate': 2.896155456223163e-07, 'fcm_dpo/beta': 0.0019028617534786463, 'fcm_dpo/q_t': 0.4004201292991638, 'fcm_dpo/delta': -0.032430313527584076, 'fcm_dpo/margin': 226.35147094726562, 'margin_dpo/margin_mean': 226.3514862060547, 'margin_dpo/margin_std': 255.4004364013672, 'logps/chosen': -372.24151611328125, 'logps/rejected': -639.7134399414062, 'logps/ref_chosen': -57.9904899597168, 'logps/ref_rejected': -99.11092376708984, 'logits/chosen': -0.44945335388183594, 'logits/rejected': -0.4429987072944641, 'epoch': 0.51}
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{'loss': 1.0959, 'grad_norm': 30.192829132080078, 'learning_rate': 2.8326761550411346e-07, 'fcm_dpo/beta': 0.0018661676440387964, 'fcm_dpo/q_t': 0.40922412276268005, 'fcm_dpo/delta': 0.005433606915175915, 'fcm_dpo/margin': 211.39328002929688, 'margin_dpo/margin_mean': 211.3932647705078, 'margin_dpo/margin_std': 280.6878967285156, 'logps/chosen': -384.77960205078125, 'logps/rejected': -627.1307373046875, 'logps/ref_chosen': -58.29923629760742, 'logps/ref_rejected': -89.25711822509766, 'logits/chosen': -0.442319393157959, 'logits/rejected': -0.4401112198829651, 'epoch': 0.51}
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{'loss': 1.0868, 'grad_norm': 37.005271911621094, 'learning_rate': 2.7689777072570284e-07, 'fcm_dpo/beta': 0.001845445716753602, 'fcm_dpo/q_t': 0.4076092839241028, 'fcm_dpo/delta': -0.019822590053081512, 'fcm_dpo/margin': 216.8295135498047, 'margin_dpo/margin_mean': 216.8295135498047, 'margin_dpo/margin_std': 270.96405029296875, 'logps/chosen': -382.65460205078125, 'logps/rejected': -624.6368408203125, 'logps/ref_chosen': -60.788482666015625, 'logps/ref_rejected': -85.94129943847656, 'logits/chosen': -0.4728454649448395, 'logits/rejected': -0.46268409490585327, 'epoch': 0.52}
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{'loss': 1.1282, 'grad_norm': 36.66780471801758, 'learning_rate': 2.7051020734928443e-07, 'fcm_dpo/beta': 0.0018649225821718574, 'fcm_dpo/q_t': 0.4203580319881439, 'fcm_dpo/delta': 0.030804917216300964, 'fcm_dpo/margin': 183.98890686035156, 'margin_dpo/margin_mean': 183.98892211914062, 'margin_dpo/margin_std': 254.2589569091797, 'logps/chosen': -384.0989074707031, 'logps/rejected': -591.0260009765625, 'logps/ref_chosen': -57.6871337890625, 'logps/ref_rejected': -80.62527465820312, 'logits/chosen': -0.4746428430080414, 'logits/rejected': -0.4617390036582947, 'epoch': 0.53}
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{'loss': 1.0628, 'grad_norm': 26.54566764831543, 'learning_rate': 2.641091331089811e-07, 'fcm_dpo/beta': 0.0018712872406467795, 'fcm_dpo/q_t': 0.40148013830184937, 'fcm_dpo/delta': -0.026755044236779213, 'fcm_dpo/margin': 227.2862091064453, 'margin_dpo/margin_mean': 227.28622436523438, 'margin_dpo/margin_std': 260.75958251953125, 'logps/chosen': -337.5777893066406, 'logps/rejected': -604.4019165039062, 'logps/ref_chosen': -51.490867614746094, 'logps/ref_rejected': -91.02871704101562, 'logits/chosen': -0.473797470331192, 'logits/rejected': -0.47837966680526733, 'epoch': 0.54}
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{'loss': 1.1143, 'grad_norm': 38.50527572631836, 'learning_rate': 2.5769876463904263e-07, 'fcm_dpo/beta': 0.0018645223462954164, 'fcm_dpo/q_t': 0.41541823744773865, 'fcm_dpo/delta': 0.038537509739398956, 'fcm_dpo/margin': 194.5872039794922, 'margin_dpo/margin_mean': 194.5872039794922, 'margin_dpo/margin_std': 256.3455505371094, 'logps/chosen': -354.23822021484375, 'logps/rejected': -580.1464233398438, 'logps/ref_chosen': -58.113502502441406, 'logps/ref_rejected': -89.43451690673828, 'logits/chosen': -0.47979289293289185, 'logits/rejected': -0.4759935438632965, 'epoch': 0.54}
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{'loss': 1.0839, 'grad_norm': 42.09442901611328, 'learning_rate': 2.512833246961859e-07, 'fcm_dpo/beta': 0.0018788978923112154, 'fcm_dpo/q_t': 0.403217077255249, 'fcm_dpo/delta': -0.028660928830504417, 'fcm_dpo/margin': 227.169677734375, 'margin_dpo/margin_mean': 227.169677734375, 'margin_dpo/margin_std': 307.71136474609375, 'logps/chosen': -409.12677001953125, 'logps/rejected': -660.3104248046875, 'logps/ref_chosen': -65.23600769042969, 'logps/ref_rejected': -89.24995422363281, 'logits/chosen': -0.5087894201278687, 'logits/rejected': -0.494729608297348, 'epoch': 0.55}
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{'loss': 1.034, 'grad_norm': 27.727758407592773, 'learning_rate': 2.4486703937790243e-07, 'fcm_dpo/beta': 0.001791507238522172, 'fcm_dpo/q_t': 0.39022326469421387, 'fcm_dpo/delta': -0.07822184264659882, 'fcm_dpo/margin': 264.9973449707031, 'margin_dpo/margin_mean': 264.9973449707031, 'margin_dpo/margin_std': 298.83721923828125, 'logps/chosen': -376.74932861328125, 'logps/rejected': -690.5615234375, 'logps/ref_chosen': -53.33893966674805, 'logps/ref_rejected': -102.15375518798828, 'logits/chosen': -0.4783501625061035, 'logits/rejected': -0.49099501967430115, 'epoch': 0.56}
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{'loss': 1.0946, 'grad_norm': 39.414588928222656, 'learning_rate': 2.3845413533856514e-07, 'fcm_dpo/beta': 0.0017382428050041199, 'fcm_dpo/q_t': 0.40880244970321655, 'fcm_dpo/delta': 0.007922522723674774, 'fcm_dpo/margin': 225.6304931640625, 'margin_dpo/margin_mean': 225.6304931640625, 'margin_dpo/margin_std': 290.14666748046875, 'logps/chosen': -414.2498474121094, 'logps/rejected': -670.964599609375, 'logps/ref_chosen': -58.36262130737305, 'logps/ref_rejected': -89.44685363769531, 'logits/chosen': -0.4913402497768402, 'logits/rejected': -0.4843069911003113, 'epoch': 0.57}
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{'loss': 1.0741, 'grad_norm': 26.369205474853516, 'learning_rate': 2.320488370051681e-07, 'fcm_dpo/beta': 0.0017035829368978739, 'fcm_dpo/q_t': 0.4024105966091156, 'fcm_dpo/delta': -0.029813114553689957, 'fcm_dpo/margin': 251.324462890625, 'margin_dpo/margin_mean': 251.324462890625, 'margin_dpo/margin_std': 322.6702575683594, 'logps/chosen': -435.18115234375, 'logps/rejected': -720.5994873046875, 'logps/ref_chosen': -56.380653381347656, 'logps/ref_rejected': -90.47447204589844, 'logits/chosen': -0.486684650182724, 'logits/rejected': -0.4810120165348053, 'epoch': 0.57}
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{'loss': 1.1036, 'grad_norm': 31.417821884155273, 'learning_rate': 2.2565536379453404e-07, 'fcm_dpo/beta': 0.0017207658383995295, 'fcm_dpo/q_t': 0.41174229979515076, 'fcm_dpo/delta': 0.012584102340042591, 'fcm_dpo/margin': 225.0916748046875, 'margin_dpo/margin_mean': 225.0916748046875, 'margin_dpo/margin_std': 308.83575439453125, 'logps/chosen': -402.8694763183594, 'logps/rejected': -659.1397705078125, 'logps/ref_chosen': -55.95304489135742, 'logps/ref_rejected': -87.13162994384766, 'logits/chosen': -0.47851499915122986, 'logits/rejected': -0.4759146273136139, 'epoch': 0.58}
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{'loss': 1.0433, 'grad_norm': 22.06127166748047, 'learning_rate': 2.192779273338215e-07, 'fcm_dpo/beta': 0.0016688309842720628, 'fcm_dpo/q_t': 0.39453184604644775, 'fcm_dpo/delta': -0.05934460088610649, 'fcm_dpo/margin': 273.747314453125, 'margin_dpo/margin_mean': 273.747314453125, 'margin_dpo/margin_std': 306.27801513671875, 'logps/chosen': -424.73455810546875, 'logps/rejected': -730.5912475585938, 'logps/ref_chosen': -64.59160614013672, 'logps/ref_rejected': -96.700927734375, 'logits/chosen': -0.48663657903671265, 'logits/rejected': -0.4787791669368744, 'epoch': 0.59}
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***** Running Evaluation *****
[INFO|trainer.py:4309] 2026-04-21 22:12:40,575 >> Num examples = 2339
[INFO|trainer.py:4312] 2026-04-21 22:12:40,575 >> Batch size = 8
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{'loss': 1.1532, 'grad_norm': 38.367191314697266, 'learning_rate': 4.375063135042445e-08, 'fcm_dpo/beta': 0.0010072619188576937, 'fcm_dpo/q_t': 0.41634687781333923, 'fcm_dpo/delta': 0.004320817068219185, 'fcm_dpo/margin': 365.18194580078125, 'margin_dpo/margin_mean': 365.18194580078125, 'margin_dpo/margin_std': 646.3736572265625, 'logps/chosen': -805.9225463867188, 'logps/rejected': -1202.0889892578125, 'logps/ref_chosen': -62.85475540161133, 'logps/ref_rejected': -93.8392105102539, 'logits/chosen': -1.0174771547317505, 'logits/rejected': -1.0257703065872192, 'epoch': 0.83}
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{'loss': 1.108, 'grad_norm': 32.0954475402832, 'learning_rate': 4.019267817841834e-08, 'fcm_dpo/beta': 0.000991632230579853, 'fcm_dpo/q_t': 0.40820297598838806, 'fcm_dpo/delta': -0.003437476698309183, 'fcm_dpo/margin': 406.2334899902344, 'margin_dpo/margin_mean': 406.2334899902344, 'margin_dpo/margin_std': 592.2410278320312, 'logps/chosen': -756.536865234375, 'logps/rejected': -1192.6998291015625, 'logps/ref_chosen': -57.98622512817383, 'logps/ref_rejected': -87.91555786132812, 'logits/chosen': -1.057476282119751, 'logits/rejected': -1.0744601488113403, 'epoch': 0.84}
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{'loss': 1.1112, 'grad_norm': 39.946693420410156, 'learning_rate': 3.677293317363864e-08, 'fcm_dpo/beta': 0.000984189915470779, 'fcm_dpo/q_t': 0.4089413583278656, 'fcm_dpo/delta': -0.0074859424494206905, 'fcm_dpo/margin': 413.28948974609375, 'margin_dpo/margin_mean': 413.28948974609375, 'margin_dpo/margin_std': 633.7578735351562, 'logps/chosen': -763.88623046875, 'logps/rejected': -1211.663818359375, 'logps/ref_chosen': -55.194114685058594, 'logps/ref_rejected': -89.68229675292969, 'logits/chosen': -1.012502908706665, 'logits/rejected': -1.0302174091339111, 'epoch': 0.84}
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{'loss': 1.1256, 'grad_norm': 36.99066925048828, 'learning_rate': 3.349364905389032e-08, 'fcm_dpo/beta': 0.0010015666484832764, 'fcm_dpo/q_t': 0.41545066237449646, 'fcm_dpo/delta': 0.005687057971954346, 'fcm_dpo/margin': 373.99749755859375, 'margin_dpo/margin_mean': 373.99749755859375, 'margin_dpo/margin_std': 568.8309326171875, 'logps/chosen': -681.4942626953125, 'logps/rejected': -1089.847412109375, 'logps/ref_chosen': -54.605796813964844, 'logps/ref_rejected': -88.9614486694336, 'logits/chosen': -0.9414408802986145, 'logits/rejected': -0.9566031694412231, 'epoch': 0.85}
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{'loss': 1.1365, 'grad_norm': 30.979644775390625, 'learning_rate': 3.035698600998121e-08, 'fcm_dpo/beta': 0.0009860583813861012, 'fcm_dpo/q_t': 0.4164944589138031, 'fcm_dpo/delta': -0.024760950356721878, 'fcm_dpo/margin': 374.35772705078125, 'margin_dpo/margin_mean': 374.35772705078125, 'margin_dpo/margin_std': 598.1573486328125, 'logps/chosen': -722.11083984375, 'logps/rejected': -1131.833984375, 'logps/ref_chosen': -59.03770065307617, 'logps/ref_rejected': -94.4029541015625, 'logits/chosen': -1.005885362625122, 'logits/rejected': -1.0213685035705566, 'epoch': 0.86}
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{'loss': 1.1114, 'grad_norm': 26.06329917907715, 'learning_rate': 2.736501028272095e-08, 'fcm_dpo/beta': 0.0009923167526721954, 'fcm_dpo/q_t': 0.41268691420555115, 'fcm_dpo/delta': 0.020330144092440605, 'fcm_dpo/margin': 382.85650634765625, 'margin_dpo/margin_mean': 382.85650634765625, 'margin_dpo/margin_std': 544.3261108398438, 'logps/chosen': -699.3173828125, 'logps/rejected': -1128.5604248046875, 'logps/ref_chosen': -53.5163688659668, 'logps/ref_rejected': -99.90290832519531, 'logits/chosen': -1.001636266708374, 'logits/rejected': -1.0243651866912842, 'epoch': 0.87}
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{'loss': 1.1503, 'grad_norm': 51.35660934448242, 'learning_rate': 2.451969280180849e-08, 'fcm_dpo/beta': 0.0009959937306120992, 'fcm_dpo/q_t': 0.4196888506412506, 'fcm_dpo/delta': 0.008491059765219688, 'fcm_dpo/margin': 356.68133544921875, 'margin_dpo/margin_mean': 356.68133544921875, 'margin_dpo/margin_std': 606.1689453125, 'logps/chosen': -701.3692626953125, 'logps/rejected': -1084.035888671875, 'logps/ref_chosen': -51.44538497924805, 'logps/ref_rejected': -77.43083190917969, 'logits/chosen': -0.9872266054153442, 'logits/rejected': -0.9868671298027039, 'epoch': 0.87}
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{'loss': 1.1393, 'grad_norm': 36.674869537353516, 'learning_rate': 2.1822907887504932e-08, 'fcm_dpo/beta': 0.0010021307971328497, 'fcm_dpo/q_t': 0.418224960565567, 'fcm_dpo/delta': 0.01705138385295868, 'fcm_dpo/margin': 358.8981018066406, 'margin_dpo/margin_mean': 358.89813232421875, 'margin_dpo/margin_std': 566.36669921875, 'logps/chosen': -721.6881103515625, 'logps/rejected': -1111.1573486328125, 'logps/ref_chosen': -57.161705017089844, 'logps/ref_rejected': -87.73274230957031, 'logits/chosen': -0.9832857251167297, 'logits/rejected': -0.9899972677230835, 'epoch': 0.88}
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***** Running Evaluation *****
[INFO|trainer.py:4309] 2026-04-21 22:21:51,798 >> Num examples = 2339
[INFO|trainer.py:4312] 2026-04-21 22:21:51,798 >> Batch size = 8
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{'eval_loss': 0.6074439883232117, 'eval_runtime': 39.7407, 'eval_samples_per_second': 58.856, 'eval_steps_per_second': 1.862, 'eval_fcm_dpo/beta': 0.0011259522289037704, 'eval_fcm_dpo/q_t': 0.4331645667552948, 'eval_fcm_dpo/delta': 0.023851953446865082, 'eval_fcm_dpo/margin': 270.7278747558594, 'eval_margin_dpo/margin_mean': 270.7278747558594, 'eval_margin_dpo/margin_std': 601.7490234375, 'eval_logps/chosen': -823.232421875, 'eval_logps/rejected': -1101.70703125, 'eval_logps/ref_chosen': -79.05104064941406, 'eval_logps/ref_rejected': -86.79793548583984, 'eval_logits/chosen': -1.0197498798370361, 'eval_logits/rejected': -1.0176793336868286, 'epoch': 0.88}
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{'loss': 1.0561, 'grad_norm': 36.93719482421875, 'learning_rate': 1.9276432015946446e-08, 'fcm_dpo/beta': 0.0011384881800040603, 'fcm_dpo/q_t': 0.39160969853401184, 'fcm_dpo/delta': -0.09710332006216049, 'fcm_dpo/margin': 432.0416564941406, 'margin_dpo/margin_mean': 432.0416564941406, 'margin_dpo/margin_std': 594.4193725585938, 'logps/chosen': -690.4810791015625, 'logps/rejected': -1159.7216796875, 'logps/ref_chosen': -58.169830322265625, 'logps/ref_rejected': -95.36891174316406, 'logits/chosen': -0.9972618222236633, 'logits/rejected': -1.01743483543396, 'epoch': 0.89}
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{'loss': 1.102, 'grad_norm': 48.549068450927734, 'learning_rate': 1.6881942648911074e-08, 'fcm_dpo/beta': 0.0010870896512642503, 'fcm_dpo/q_t': 0.4077000617980957, 'fcm_dpo/delta': -0.01724116876721382, 'fcm_dpo/margin': 382.8441467285156, 'margin_dpo/margin_mean': 382.8440856933594, 'margin_dpo/margin_std': 576.8626708984375, 'logps/chosen': -703.338623046875, 'logps/rejected': -1116.2406005859375, 'logps/ref_chosen': -58.97087860107422, 'logps/ref_rejected': -89.0286865234375, 'logits/chosen': -0.9739276766777039, 'logits/rejected': -0.978052020072937, 'epoch': 0.9}
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{'loss': 1.0677, 'grad_norm': 26.998958587646484, 'learning_rate': 1.4641017128809801e-08, 'fcm_dpo/beta': 0.001023916294798255, 'fcm_dpo/q_t': 0.39545583724975586, 'fcm_dpo/delta': -0.07400115579366684, 'fcm_dpo/margin': 458.7464294433594, 'margin_dpo/margin_mean': 458.7464904785156, 'margin_dpo/margin_std': 639.427734375, 'logps/chosen': -723.0494384765625, 'logps/rejected': -1219.635498046875, 'logps/ref_chosen': -58.081878662109375, 'logps/ref_rejected': -95.92155456542969, 'logits/chosen': -0.9687691926956177, 'logits/rejected': -1.0111548900604248, 'epoch': 0.9}
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{'loss': 1.1594, 'grad_norm': 31.997928619384766, 'learning_rate': 1.2555131639630567e-08, 'fcm_dpo/beta': 0.0010129540460184216, 'fcm_dpo/q_t': 0.4198682904243469, 'fcm_dpo/delta': 0.012466437183320522, 'fcm_dpo/margin': 362.10418701171875, 'margin_dpo/margin_mean': 362.10418701171875, 'margin_dpo/margin_std': 658.1754150390625, 'logps/chosen': -801.2032470703125, 'logps/rejected': -1181.641357421875, 'logps/ref_chosen': -62.203094482421875, 'logps/ref_rejected': -80.53683471679688, 'logits/chosen': -0.9928318858146667, 'logits/rejected': -0.9981027841567993, 'epoch': 0.91}
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{'loss': 1.0786, 'grad_norm': 67.80354309082031, 'learning_rate': 1.0625660234518913e-08, 'fcm_dpo/beta': 0.0009900578297674656, 'fcm_dpo/q_t': 0.4008522033691406, 'fcm_dpo/delta': -0.04029404744505882, 'fcm_dpo/margin': 442.16802978515625, 'margin_dpo/margin_mean': 442.1680603027344, 'margin_dpo/margin_std': 596.7000732421875, 'logps/chosen': -743.4299926757812, 'logps/rejected': -1212.309326171875, 'logps/ref_chosen': -61.727455139160156, 'logps/ref_rejected': -88.4387435913086, 'logits/chosen': -0.9926285743713379, 'logits/rejected': -1.0111424922943115, 'epoch': 0.92}
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{'loss': 1.1426, 'grad_norm': 57.19618225097656, 'learning_rate': 8.85387393063622e-09, 'fcm_dpo/beta': 0.0009705528500489891, 'fcm_dpo/q_t': 0.41799044609069824, 'fcm_dpo/delta': -0.0021920218132436275, 'fcm_dpo/margin': 385.10406494140625, 'margin_dpo/margin_mean': 385.10406494140625, 'margin_dpo/margin_std': 646.9403076171875, 'logps/chosen': -764.3931884765625, 'logps/rejected': -1184.7386474609375, 'logps/ref_chosen': -61.30865478515625, 'logps/ref_rejected': -96.54997253417969, 'logits/chosen': -0.981094479560852, 'logits/rejected': -0.999189019203186, 'epoch': 0.93}
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{'loss': 1.1768, 'grad_norm': 41.87347412109375, 'learning_rate': 7.240939871891699e-09, 'fcm_dpo/beta': 0.000991217908449471, 'fcm_dpo/q_t': 0.42787250876426697, 'fcm_dpo/delta': 0.04439081624150276, 'fcm_dpo/margin': 321.2152099609375, 'margin_dpo/margin_mean': 321.2152404785156, 'margin_dpo/margin_std': 599.1561889648438, 'logps/chosen': -819.9927978515625, 'logps/rejected': -1167.1407470703125, 'logps/ref_chosen': -63.7315673828125, 'logps/ref_rejected': -89.66435241699219, 'logits/chosen': -1.0177139043807983, 'logits/rejected': -1.0183391571044922, 'epoch': 0.93}
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{'loss': 1.1439, 'grad_norm': 40.166175842285156, 'learning_rate': 5.7879205600998296e-09, 'fcm_dpo/beta': 0.0009926257189363241, 'fcm_dpo/q_t': 0.41502299904823303, 'fcm_dpo/delta': -0.05684474855661392, 'fcm_dpo/margin': 380.9329528808594, 'margin_dpo/margin_mean': 380.9329528808594, 'margin_dpo/margin_std': 651.566162109375, 'logps/chosen': -797.8259887695312, 'logps/rejected': -1208.0919189453125, 'logps/ref_chosen': -59.17915725708008, 'logps/ref_rejected': -88.51210021972656, 'logits/chosen': -0.9638550877571106, 'logits/rejected': -0.9688556790351868, 'epoch': 0.94}
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{'loss': 1.1994, 'grad_norm': 79.06712341308594, 'learning_rate': 4.495773155069299e-09, 'fcm_dpo/beta': 0.0009744317503646016, 'fcm_dpo/q_t': 0.43180274963378906, 'fcm_dpo/delta': 0.0341024175286293, 'fcm_dpo/margin': 321.48162841796875, 'margin_dpo/margin_mean': 321.48162841796875, 'margin_dpo/margin_std': 670.0167846679688, 'logps/chosen': -791.4851684570312, 'logps/rejected': -1147.3848876953125, 'logps/ref_chosen': -59.50596237182617, 'logps/ref_rejected': -93.92404174804688, 'logits/chosen': -0.9938424229621887, 'logits/rejected': -1.0045819282531738, 'epoch': 0.95}
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{'loss': 1.1354, 'grad_norm': 39.774078369140625, 'learning_rate': 3.3653488440851253e-09, 'fcm_dpo/beta': 0.0009998297318816185, 'fcm_dpo/q_t': 0.41648992896080017, 'fcm_dpo/delta': 0.0030700929928570986, 'fcm_dpo/margin': 377.16595458984375, 'margin_dpo/margin_mean': 377.16595458984375, 'margin_dpo/margin_std': 618.4581298828125, 'logps/chosen': -719.2337036132812, 'logps/rejected': -1128.2410888671875, 'logps/ref_chosen': -57.774566650390625, 'logps/ref_rejected': -89.61600494384766, 'logits/chosen': -0.994001567363739, 'logits/rejected': -1.0127675533294678, 'epoch': 0.95}
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{'loss': 1.1068, 'grad_norm': 35.741294860839844, 'learning_rate': 2.397392281198729e-09, 'fcm_dpo/beta': 0.0009819023543968797, 'fcm_dpo/q_t': 0.41048040986061096, 'fcm_dpo/delta': 0.001074020517989993, 'fcm_dpo/margin': 406.14300537109375, 'margin_dpo/margin_mean': 406.1430358886719, 'margin_dpo/margin_std': 598.8343505859375, 'logps/chosen': -682.8621826171875, 'logps/rejected': -1135.7293701171875, 'logps/ref_chosen': -55.68403244018555, 'logps/ref_rejected': -102.4081802368164, 'logits/chosen': -1.0151567459106445, 'logits/rejected': -1.0480637550354004, 'epoch': 0.96}
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{'loss': 1.0617, 'grad_norm': 36.36381149291992, 'learning_rate': 1.592541096695571e-09, 'fcm_dpo/beta': 0.0009497703285887837, 'fcm_dpo/q_t': 0.39766284823417664, 'fcm_dpo/delta': -0.056020140647888184, 'fcm_dpo/margin': 475.952880859375, 'margin_dpo/margin_mean': 475.95281982421875, 'margin_dpo/margin_std': 605.3031005859375, 'logps/chosen': -716.3291625976562, 'logps/rejected': -1227.274169921875, 'logps/ref_chosen': -59.19981002807617, 'logps/ref_rejected': -94.19200134277344, 'logits/chosen': -0.988078773021698, 'logits/rejected': -1.017830491065979, 'epoch': 0.97}
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{'loss': 1.1093, 'grad_norm': 40.71209716796875, 'learning_rate': 9.513254770636137e-10, 'fcm_dpo/beta': 0.0009469041833654046, 'fcm_dpo/q_t': 0.41134023666381836, 'fcm_dpo/delta': 0.0041985055431723595, 'fcm_dpo/margin': 417.9197692871094, 'margin_dpo/margin_mean': 417.9197692871094, 'margin_dpo/margin_std': 626.8549194335938, 'logps/chosen': -698.357421875, 'logps/rejected': -1150.887451171875, 'logps/ref_chosen': -61.2533073425293, 'logps/ref_rejected': -95.86351013183594, 'logits/chosen': -1.0182468891143799, 'logits/rejected': -1.0391613245010376, 'epoch': 0.98}
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{'loss': 1.1, 'grad_norm': 29.223600387573242, 'learning_rate': 4.741678157389739e-10, 'fcm_dpo/beta': 0.0009450761717744172, 'fcm_dpo/q_t': 0.40688472986221313, 'fcm_dpo/delta': -0.012223686091601849, 'fcm_dpo/margin': 435.3887634277344, 'margin_dpo/margin_mean': 435.3887634277344, 'margin_dpo/margin_std': 627.5145263671875, 'logps/chosen': -724.4750366210938, 'logps/rejected': -1189.3773193359375, 'logps/ref_chosen': -62.95263671875, 'logps/ref_rejected': -92.4662094116211, 'logits/chosen': -0.9618457555770874, 'logits/rejected': -0.9741120338439941, 'epoch': 0.98}
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{'loss': 1.1069, 'grad_norm': 23.441814422607422, 'learning_rate': 1.6138243485910863e-10, 'fcm_dpo/beta': 0.000940955535043031, 'fcm_dpo/q_t': 0.4094417095184326, 'fcm_dpo/delta': -0.006233499385416508, 'fcm_dpo/margin': 431.116455078125, 'margin_dpo/margin_mean': 431.116455078125, 'margin_dpo/margin_std': 644.87255859375, 'logps/chosen': -741.0542602539062, 'logps/rejected': -1204.8636474609375, 'logps/ref_chosen': -48.5856819152832, 'logps/ref_rejected': -81.27871704101562, 'logits/chosen': -1.0078109502792358, 'logits/rejected': -1.02387535572052, 'epoch': 0.99}
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{'loss': 1.0916, 'grad_norm': 31.682743072509766, 'learning_rate': 1.31753782067201e-11, 'fcm_dpo/beta': 0.0009158365428447723, 'fcm_dpo/q_t': 0.40588778257369995, 'fcm_dpo/delta': -0.01913156732916832, 'fcm_dpo/margin': 456.44354248046875, 'margin_dpo/margin_mean': 456.44354248046875, 'margin_dpo/margin_std': 645.1212768554688, 'logps/chosen': -744.6751708984375, 'logps/rejected': -1228.09912109375, 'logps/ref_chosen': -60.25421905517578, 'logps/ref_rejected': -87.23457336425781, 'logits/chosen': -0.9820996522903442, 'logits/rejected': -0.9966181516647339, 'epoch': 1.0}
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100%|██████████| 681/681 [30:54<00:00, 2.55s/it][INFO|trainer.py:2681] 2026-04-21 22:25:57,730 >>
Training completed. Do not forget to share your model on huggingface.co/models =)
{'train_runtime': 1861.3017, 'train_samples_per_second': 23.423, 'train_steps_per_second': 0.366, 'train_loss': 1.1011297496229893, 'epoch': 1.0}
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***** train metrics *****
epoch = 1.0
total_flos = 0GF
train_loss = 1.1011
train_runtime = 0:31:01.30
train_samples = 43598
train_samples_per_second = 23.423
train_steps_per_second = 0.366
2026-04-21 22:25:57 - INFO - __main__ - *** Training complete ***
2026-04-21 22:25:57 - INFO - __main__ - *** Save model ***
[INFO|configuration_utils.py:419] 2026-04-21 22:26:33,935 >> Configuration saved in /root/dynamic-dpo-v4/outputs/llama-3-8b-base-new-dpo-hh-helpful-s_star0.4-4xh200-batch-64-20260421-214335-rerun/config.json
[INFO|configuration_utils.py:911] 2026-04-21 22:26:33,935 >> Configuration saved in /root/dynamic-dpo-v4/outputs/llama-3-8b-base-new-dpo-hh-helpful-s_star0.4-4xh200-batch-64-20260421-214335-rerun/generation_config.json
[INFO|modeling_utils.py:3580] 2026-04-21 22:27:01,592 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 7 checkpoint shards. You can find where each parameters has been saved in the index located at /root/dynamic-dpo-v4/outputs/llama-3-8b-base-new-dpo-hh-helpful-s_star0.4-4xh200-batch-64-20260421-214335-rerun/model.safetensors.index.json.
[INFO|tokenization_utils_base.py:2510] 2026-04-21 22:27:01,595 >> tokenizer config file saved in /root/dynamic-dpo-v4/outputs/llama-3-8b-base-new-dpo-hh-helpful-s_star0.4-4xh200-batch-64-20260421-214335-rerun/tokenizer_config.json
[INFO|tokenization_utils_base.py:2519] 2026-04-21 22:27:01,595 >> Special tokens file saved in /root/dynamic-dpo-v4/outputs/llama-3-8b-base-new-dpo-hh-helpful-s_star0.4-4xh200-batch-64-20260421-214335-rerun/special_tokens_map.json
2026-04-21 22:27:01 - INFO - __main__ - Saved HF-compatible model artifacts to /root/dynamic-dpo-v4/outputs/llama-3-8b-base-new-dpo-hh-helpful-s_star0.4-4xh200-batch-64-20260421-214335-rerun
[INFO|modelcard.py:450] 2026-04-21 22:27:03,638 >> Dropping the following result as it does not have all the necessary fields:
{'dataset': {'name': 'Anthropic/hh-rlhf', 'type': 'Anthropic/hh-rlhf'}}
[INFO|configuration_utils.py:419] 2026-04-21 22:27:03,642 >> Configuration saved in /root/dynamic-dpo-v4/outputs/llama-3-8b-base-new-dpo-hh-helpful-s_star0.4-4xh200-batch-64-20260421-214335-rerun/config.json
2026-04-21 22:27:03 - INFO - __main__ - *** Evaluate ***
[INFO|trainer.py:4307] 2026-04-21 22:27:03,643 >>
***** Running Evaluation *****
[INFO|trainer.py:4309] 2026-04-21 22:27:03,644 >> Num examples = 2339
[INFO|trainer.py:4312] 2026-04-21 22:27:03,644 >> Batch size = 8
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***** eval metrics *****
epoch = 1.0
eval_fcm_dpo/beta = 0.0011
eval_fcm_dpo/delta = 0.0295
eval_fcm_dpo/margin = 286.2177
eval_fcm_dpo/q_t = 0.4339
eval_logits/chosen = -1.0338
eval_logits/rejected = -1.0381
eval_logps/chosen = -853.6937
eval_logps/ref_chosen = -79.051
eval_logps/ref_rejected = -86.7979
eval_logps/rejected = -1147.6583
eval_loss = 0.6072
eval_margin_dpo/margin_mean = 286.2177
eval_margin_dpo/margin_std = 631.6003
eval_runtime = 0:00:39.58
eval_samples = 2339
eval_samples_per_second = 59.083
eval_steps_per_second = 1.869
2026-04-21 22:27:43 - INFO - __main__ - Pushing to hub...
2026-04-21 22:27:43 - INFO - __main__ - Uploading validated model artifacts from /root/dynamic-dpo-v4/outputs/llama-3-8b-base-new-dpo-hh-helpful-s_star0.4-4xh200-batch-64-20260421-214335-rerun to jackf857/llama-3-8b-base-new-dpo-hh-helpful-s_star0.4-4xh200-batch-64-20260421-214335-rerun
It seems you are trying to upload a large folder at once. This might take some time and then fail if the folder is too large. For such cases, it is recommended to upload in smaller batches or to use `HfApi().upload_large_folder(...)`/`huggingface-cli upload-large-folder` instead. For more details, check out https://huggingface.co/docs/huggingface_hub/main/en/guides/upload#upload-a-large-folder.
2026-04-21 22:27:43 - WARNING - huggingface_hub.hf_api - It seems you are trying to upload a large folder at once. This might take some time and then fail if the folder is too large. For such cases, it is recommended to upload in smaller batches or to use `HfApi().upload_large_folder(...)`/`huggingface-cli upload-large-folder` instead. For more details, check out https://huggingface.co/docs/huggingface_hub/main/en/guides/upload#upload-a-large-folder.
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