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--- |
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base_model: meta-llama/Meta-Llama-3-8B-Instruct |
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library_name: peft |
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license: llama3 |
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metrics: |
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- accuracy |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: reward_model |
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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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# reward_model |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7036 |
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- Accuracy: 0.5236 |
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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-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.02 |
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- num_epochs: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.7293 | 0.08 | 128 | 0.7252 | 0.4850 | |
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| 0.7412 | 0.15 | 256 | 0.6925 | 0.5386 | |
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| 0.7182 | 0.23 | 384 | 0.6954 | 0.5327 | |
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| 0.6997 | 0.3 | 512 | 0.6941 | 0.5277 | |
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| 0.7547 | 0.38 | 640 | 0.6959 | 0.5279 | |
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| 0.7123 | 0.45 | 768 | 0.6993 | 0.5252 | |
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| 0.7281 | 0.53 | 896 | 0.6962 | 0.5275 | |
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| 0.7169 | 0.6 | 1024 | 0.6986 | 0.5156 | |
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| 0.7244 | 0.68 | 1152 | 0.6981 | 0.5125 | |
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| 0.7199 | 0.75 | 1280 | 0.7000 | 0.5060 | |
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| 0.7311 | 0.83 | 1408 | 0.6959 | 0.5140 | |
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| 0.7123 | 0.9 | 1536 | 0.6956 | 0.5154 | |
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| 0.7344 | 0.98 | 1664 | 0.6970 | 0.5100 | |
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| 0.7105 | 1.05 | 1792 | 0.6933 | 0.5219 | |
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| 0.6947 | 1.13 | 1920 | 0.6944 | 0.5259 | |
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| 0.7261 | 1.21 | 2048 | 0.6960 | 0.5256 | |
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| 0.6997 | 1.28 | 2176 | 0.6974 | 0.5188 | |
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| 0.7442 | 1.36 | 2304 | 0.6960 | 0.5163 | |
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| 0.7004 | 1.43 | 2432 | 0.6987 | 0.5286 | |
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| 0.7089 | 1.51 | 2560 | 0.6982 | 0.5288 | |
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| 0.7142 | 1.58 | 2688 | 0.7014 | 0.5154 | |
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| 0.7364 | 1.66 | 2816 | 0.6997 | 0.5202 | |
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| 0.6915 | 1.73 | 2944 | 0.7043 | 0.5200 | |
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| 0.7322 | 1.81 | 3072 | 0.7037 | 0.5229 | |
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| 0.7524 | 1.88 | 3200 | 0.7019 | 0.5219 | |
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| 0.7192 | 1.96 | 3328 | 0.7036 | 0.5236 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.36.0 |
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- Pytorch 2.2.0 |
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- Datasets 2.20.0 |
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- Tokenizers 0.15.2 |
