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--- |
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license: llama3.1 |
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base_model: meta-llama/Llama-3.1-8B-Instruct |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: llama3_rm |
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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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# llama3_rm |
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This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3742 |
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- Accuracy: 0.8948 |
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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-06 |
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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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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 256 |
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- total_eval_batch_size: 32 |
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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: 0.03 |
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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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| 0.6626 | 0.0705 | 10 | 0.5923 | 0.6719 | |
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| 0.5039 | 0.1410 | 20 | 0.5139 | 0.7568 | |
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| 0.4865 | 0.2115 | 30 | 0.4816 | 0.7646 | |
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| 0.4814 | 0.2819 | 40 | 0.4566 | 0.7891 | |
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| 0.4932 | 0.3524 | 50 | 0.4449 | 0.7979 | |
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| 0.4723 | 0.4229 | 60 | 0.4267 | 0.8031 | |
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| 0.3906 | 0.4934 | 70 | 0.4042 | 0.8208 | |
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| 0.3418 | 0.5639 | 80 | 0.3907 | 0.8245 | |
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| 0.4427 | 0.6344 | 90 | 0.3736 | 0.8359 | |
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| 0.4022 | 0.7048 | 100 | 0.3578 | 0.8484 | |
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| 0.3738 | 0.7753 | 110 | 0.3470 | 0.8542 | |
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| 0.3619 | 0.8458 | 120 | 0.3328 | 0.8609 | |
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| 0.3266 | 0.9163 | 130 | 0.3256 | 0.8651 | |
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| 0.2786 | 0.9868 | 140 | 0.3245 | 0.8693 | |
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| 0.1685 | 1.0573 | 150 | 0.4035 | 0.8786 | |
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| 0.0421 | 1.1278 | 160 | 0.4395 | 0.8823 | |
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| 0.0655 | 1.1982 | 170 | 0.3843 | 0.8828 | |
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| 0.0734 | 1.2687 | 180 | 0.3645 | 0.8823 | |
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| 0.1441 | 1.3392 | 190 | 0.4277 | 0.8833 | |
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| 0.1176 | 1.4097 | 200 | 0.4040 | 0.8896 | |
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| 0.0826 | 1.4802 | 210 | 0.3609 | 0.8870 | |
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| 0.056 | 1.5507 | 220 | 0.3542 | 0.8891 | |
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| 0.0487 | 1.6211 | 230 | 0.3668 | 0.8927 | |
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| 0.0815 | 1.6916 | 240 | 0.3735 | 0.8938 | |
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| 0.0842 | 1.7621 | 250 | 0.3751 | 0.8943 | |
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| 0.0868 | 1.8326 | 260 | 0.3758 | 0.8932 | |
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| 0.0743 | 1.9031 | 270 | 0.3753 | 0.8938 | |
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| 0.0874 | 1.9736 | 280 | 0.3742 | 0.8948 | |
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### Framework versions |
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- Transformers 4.43.4 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 4.4.1 |
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- Tokenizers 0.19.1 |
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