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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: axolotl-ai-co/gpt-oss-20b-dequantized |
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tags: |
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- generated_from_trainer |
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datasets: |
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- HuggingFaceH4/Multilingual-Thinking |
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model-index: |
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- name: outputs/gpt-oss-20b/ |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<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) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.12.0` |
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```yaml |
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# the original mxfp4 quantized model is not supported with FSDP cpu_ram_efficient_loading |
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# FSDP cpu_ram_efficient_loading is used to reduce the initial CPU memory usage when loading the model |
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base_model: axolotl-ai-co/gpt-oss-20b-dequantized |
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use_kernels: false |
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dp_shard_size: 8 # requires 2x8xH100 nodes |
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plugins: |
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- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin |
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experimental_skip_move_to_device: true # prevent OOM by NOT putting model to GPU before sharding |
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datasets: |
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- path: HuggingFaceH4/Multilingual-Thinking |
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type: chat_template |
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field_thinking: thinking |
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template_thinking_key: thinking |
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dataset_prepared_path: last_run_prepared |
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val_set_size: 0 |
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output_dir: ./outputs/gpt-oss-20b/ |
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#save_only_model: true |
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sequence_len: 4096 |
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sample_packing: true |
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pad_to_sequence_len: true |
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wandb_project: gpt-oss-20b |
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wandb_name: fft-20b |
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gradient_accumulation_steps: 1 |
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micro_batch_size: 4 |
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num_epochs: 1 |
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optimizer: adamw_torch_fused # 8bit optimizers do not work with FSDP2 offload |
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lr_scheduler: constant_with_warmup |
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learning_rate: 2e-5 |
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load_best_model_at_end: false |
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bf16: true |
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tf32: true |
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flash_attention: true |
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attn_implementation: kernels-community/vllm-flash-attn3 |
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gradient_checkpointing: true |
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activation_offloading: true |
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logging_steps: 1 |
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saves_per_epoch: 1 |
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warmup_ratio: 0.03 |
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special_tokens: |
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eot_tokens: |
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- "<|end|>" |
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#deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json |
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fsdp_version: 2 |
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fsdp_config: |
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offload_params: true |
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state_dict_type: SHARDED_STATE_DICT |
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auto_wrap_policy: TRANSFORMER_BASED_WRAP |
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transformer_layer_cls_to_wrap: GptOssDecoderLayer |
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reshard_after_forward: true |
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cpu_ram_efficient_loading: true |
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``` |
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</details><br> |
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# outputs/gpt-oss-20b/ |
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This model is a fine-tuned version of [axolotl-ai-co/gpt-oss-20b-dequantized](https://huggingface.co/axolotl-ai-co/gpt-oss-20b-dequantized) on the HuggingFaceH4/Multilingual-Thinking dataset. |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 32 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: constant_with_warmup |
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- training_steps: 8 |
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### Training results |
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### Framework versions |
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- Transformers 4.55.0 |
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- Pytorch 2.8.0+cu128 |
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- Datasets 4.0.0 |
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- Tokenizers 0.21.4 |
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