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--- |
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library_name: transformers |
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license: llama3.2 |
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base_model: tanliboy/llama-3.2-3b |
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tags: |
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- trl |
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- sft |
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- alignment-handbook |
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- generated_from_trainer |
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model-index: |
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- name: llama-3.2-3b-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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# llama-3.2-3b-sft |
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This model is a fine-tuned version of [tanliboy/llama-3.2-3b](https://huggingface.co/tanliboy/llama-3.2-3b) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7216 |
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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: 3e-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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.8741 | 0.0448 | 100 | 0.8600 | |
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| 0.8038 | 0.0897 | 200 | 0.8095 | |
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| 0.7937 | 0.1345 | 300 | 0.7789 | |
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| 0.7712 | 0.1794 | 400 | 0.7644 | |
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| 0.7393 | 0.2242 | 500 | 0.7565 | |
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| 0.7458 | 0.2691 | 600 | 0.7506 | |
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| 0.7694 | 0.3139 | 700 | 0.7458 | |
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| 0.713 | 0.3587 | 800 | 0.7422 | |
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| 0.7347 | 0.4036 | 900 | 0.7387 | |
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| 0.7243 | 0.4484 | 1000 | 0.7356 | |
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| 0.7161 | 0.4933 | 1100 | 0.7331 | |
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| 0.7247 | 0.5381 | 1200 | 0.7308 | |
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| 0.7477 | 0.5830 | 1300 | 0.7288 | |
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| 0.7429 | 0.6278 | 1400 | 0.7273 | |
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| 0.7317 | 0.6726 | 1500 | 0.7256 | |
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| 0.7226 | 0.7175 | 1600 | 0.7243 | |
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| 0.695 | 0.7623 | 1700 | 0.7234 | |
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| 0.7167 | 0.8072 | 1800 | 0.7226 | |
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| 0.686 | 0.8520 | 1900 | 0.7221 | |
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| 0.7214 | 0.8969 | 2000 | 0.7218 | |
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| 0.7358 | 0.9417 | 2100 | 0.7216 | |
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| 0.7259 | 0.9865 | 2200 | 0.7216 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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