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--- |
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license: llama3 |
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base_model: meta-llama/Meta-Llama-3-8B |
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tags: |
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- trl |
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- reward-trainer |
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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: rm_llama3_8B_helpsteer2 |
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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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# rm_llama3_8B_helpsteer2 |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1203 |
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- Accuracy: 0.6339 |
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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: 1e-05 |
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- train_batch_size: 32 |
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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_steps: 10 |
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- num_epochs: 3 |
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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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| 0.8471 | 0.1572 | 50 | 0.7326 | 0.5819 | |
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| 0.7455 | 0.3145 | 100 | 0.6821 | 0.5549 | |
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| 0.7059 | 0.4717 | 150 | 0.6642 | 0.6050 | |
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| 0.6926 | 0.6289 | 200 | 0.6707 | 0.5915 | |
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| 0.6683 | 0.7862 | 250 | 0.6506 | 0.6320 | |
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| 0.6727 | 0.9434 | 300 | 0.6456 | 0.6224 | |
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| 0.629 | 1.1006 | 350 | 0.6218 | 0.6551 | |
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| 0.5446 | 1.2579 | 400 | 0.6604 | 0.6281 | |
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| 0.5377 | 1.4151 | 450 | 0.6345 | 0.6455 | |
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| 0.5555 | 1.5723 | 500 | 0.6145 | 0.6320 | |
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| 0.5645 | 1.7296 | 550 | 0.6178 | 0.6474 | |
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| 0.5392 | 1.8868 | 600 | 0.6323 | 0.6532 | |
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| 0.4505 | 2.0440 | 650 | 0.7539 | 0.6455 | |
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| 0.1406 | 2.2013 | 700 | 1.0884 | 0.6339 | |
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| 0.1487 | 2.3585 | 750 | 1.1136 | 0.6339 | |
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| 0.1493 | 2.5157 | 800 | 1.1202 | 0.6358 | |
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| 0.1259 | 2.6730 | 850 | 1.1253 | 0.6320 | |
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| 0.1382 | 2.8302 | 900 | 1.1189 | 0.6320 | |
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| 0.1448 | 2.9874 | 950 | 1.1203 | 0.6339 | |
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### Framework versions |
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- Transformers 4.43.4 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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