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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: 0.3581 |
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- Accuracy: 0.8443 |
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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: 1 |
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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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| 0.8063 | 0.0705 | 10 | 0.6141 | 0.7339 | |
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| 0.5355 | 0.1410 | 20 | 0.5117 | 0.7604 | |
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| 0.4811 | 0.2115 | 30 | 0.4766 | 0.7719 | |
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| 0.4922 | 0.2819 | 40 | 0.4512 | 0.7792 | |
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| 0.4919 | 0.3524 | 50 | 0.4428 | 0.8 | |
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| 0.476 | 0.4229 | 60 | 0.4174 | 0.8083 | |
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| 0.3965 | 0.4934 | 70 | 0.4047 | 0.8161 | |
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| 0.3523 | 0.5639 | 80 | 0.3918 | 0.8224 | |
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| 0.455 | 0.6344 | 90 | 0.3794 | 0.8344 | |
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| 0.4096 | 0.7048 | 100 | 0.3682 | 0.8396 | |
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| 0.3726 | 0.7753 | 110 | 0.3636 | 0.8417 | |
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| 0.3802 | 0.8458 | 120 | 0.3600 | 0.8448 | |
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| 0.3908 | 0.9163 | 130 | 0.3585 | 0.8427 | |
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| 0.4002 | 0.9868 | 140 | 0.3581 | 0.8443 | |
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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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