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--- |
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library_name: transformers |
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license: other |
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base_model: Qwen/Qwen2.5-3B |
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tags: |
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- axolotl |
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- generated_from_trainer |
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datasets: |
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- allenai/tulu-3-sft-mixture |
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model-index: |
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- name: II-Tulu-3B-SFT |
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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: `0.5.3.dev0` |
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```yaml |
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wandb_project: llm-training-platform |
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wandb_name: II-Tulu-3B-SFT |
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datasets: |
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- path: allenai/tulu-3-sft-mixture |
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split: train |
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type: chat_template |
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field_messages: messages |
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message_field_role: role |
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message_field_content: content |
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roles: |
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system: |
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- system |
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user: |
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- user |
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assistant: |
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- assistant |
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chat_template: qwen_25 |
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sequence_len: 2048 |
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base_model: Qwen/Qwen2.5-3B |
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output_dir: checkpoints/1357e2cd-76bc-46d5-a394-949b712427c7 |
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dataset_prepared_path: checkpoints/1357e2cd-76bc-46d5-a394-949b712427c7/dataset_prepared |
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flash_attention: true |
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train_on_inputs: false |
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pad_to_sequence_len: true |
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eval_sample_packing: false |
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push_to_hub: true |
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bf16: auto |
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gradient_checkpointing: true |
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logging_steps: 10 |
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hub_model_id: phunguyen01/II-Tulu-3B-SFT |
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learning_rate: 5.0e-06 |
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micro_batch_size: 8 |
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num_epochs: 2 |
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seed: 42 |
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gradient_accumulation_steps: 2 |
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sample_packing: true |
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val_set_size: 0 |
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``` |
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</details><br> |
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# II-Tulu-3B-SFT |
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This model is a fine-tuned version of [Qwen/Qwen2.5-3B](https://huggingface.co/Qwen/Qwen2.5-3B) on the allenai/tulu-3-sft-mixture 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: 5e-06 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 64 |
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- optimizer: Use adamw_hf with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 2 |
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### Training results |
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### Framework versions |
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- Transformers 4.47.0 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.21.0 |
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