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Model: ccarrillomanzanares/ccmai
Source: Original Platform

README.md.bck

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+---
+library_name: transformers
+tags:
+- generated_from_trainer
+datasets:
+- gs://fine-tuning-634768b5-ef69-4ea6-9fd2-c9379a5ee381/copymediadatatask/execution_artifacts/clean_train.jsonl
+model-index:
+- name: tmp/output_dir/gcs/fine-tuning-634768b5-ef69-4ea6-9fd2-c9379a5ee381/postprocess/node-0/checkpoints/final
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.13.0.dev0`
+```yaml
+base_model: gs://vertex-model-garden-restricted-us/gemma3/gemma-3-12b-it
+
+# gemma3 doesn't seem to play nice with ddp
+ddp_find_unused_parameters: true
+experimental_skip_move_to_device: true  # prevent OOM by NOT putting model to GPU before sharding
+
+plugins:
+- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
+- axolotl.integrations.liger.LigerPlugin
+liger_rope: true
+liger_rms_norm: true
+liger_glu_activation: true
+liger_layer_norm: true
+liger_fused_linear_cross_entropy: true
+
+chat_template: gemma3
+eot_tokens:
+- <end_of_turn>
+
+dataset_prepared_path: last_run_prepared
+output_dir: /workspace/outputs/out
+
+sequence_len: 8192
+sample_packing: true
+eval_sample_packing: false
+
+use_kernels: true
+
+micro_batch_size: 2
+gradient_accumulation_steps: 1
+num_epochs: 3
+optimizer: adamw_torch_fused
+learning_rate: 1e-5
+
+lr_scheduler: cosine
+
+bf16: true
+tf32: true
+logging_steps: 1
+flash_attention: true
+
+gradient_checkpointing: true
+activation_offloading: true
+
+val_set_size: 0
+eval_strategy: "epoch"
+save_strategy: 'no'
+include_tokens_per_second: true
+save_safetensors: true
+use_tensorboard: true
+
+fsdp_version: 1
+fsdp_config:
+  fsdp_limit_all_gathers: true
+  fsdp_sync_module_states: true
+  fsdp_offload_params: true
+  fsdp_use_orig_params: false
+  fsdp_cpu_ram_efficient_loading: true
+  fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
+  fsdp_transformer_layer_cls_to_wrap: Gemma3DecoderLayer
+  fsdp_state_dict_type: SHARDED_STATE_DICT
+  fsdp_sharding_strategy: SHARD_GRAD_OP
+  fsdp_backward_prefetch: BACKWARD_PRE
+  final_state_dict_type: FULL_STATE_DICT
+
+```
+
+</details><br>
+
+# tmp/output_dir/gcs/fine-tuning-634768b5-ef69-4ea6-9fd2-c9379a5ee381/postprocess/node-0/checkpoints/final
+
+This model was trained from scratch on the gs://fine-tuning-634768b5-ef69-4ea6-9fd2-c9379a5ee381/copymediadatatask/execution_artifacts/clean_train.jsonl 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-07
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- total_train_batch_size: 16
+- total_eval_batch_size: 16
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 20
+- training_steps: 675
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.55.4
+- Pytorch 2.7.1+cu126
+- Datasets 4.0.0
+- Tokenizers 0.21.4