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--- |
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base_model: yentinglin/Llama-3-Taiwan-8B-Instruct |
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library_name: peft |
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license: llama3 |
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tags: |
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- trl |
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- sft |
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- generated_from_trainer |
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model-index: |
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- name: ADL_Llama |
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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/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/djengo890-national-taiwan-university/ADL_Llama/runs/d7j4fkwy) |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/djengo890-national-taiwan-university/ADL_Llama/runs/d7j4fkwy) |
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# ADL_Llama |
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This model is a fine-tuned version of [yentinglin/Llama-3-Taiwan-8B-Instruct](https://huggingface.co/yentinglin/Llama-3-Taiwan-8B-Instruct) on an unknown 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: 0.0001 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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- optimizer: Use paged_adamw_8bit 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: 50 |
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- training_steps: 3000 |
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### Framework versions |
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- PEFT 0.13.2 |
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- Transformers 4.46.1 |
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- Pytorch 2.5.0+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.1 |
