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--- |
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library_name: transformers |
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license: llama3.2 |
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base_model: meta-llama/Llama-3.2-3B-Instruct |
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tags: |
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- trl |
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- orpo |
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- generated_from_trainer |
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model-index: |
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- name: results |
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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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# results |
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This model is a fine-tuned version of [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7838 |
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- Rewards/chosen: -0.0726 |
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- Rewards/rejected: -0.1414 |
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- Rewards/accuracies: 1.0 |
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- Rewards/margins: 0.0688 |
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- Logps/rejected: -1.4145 |
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- Logps/chosen: -0.7263 |
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- Logits/rejected: -1.3572 |
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- Logits/chosen: -1.0579 |
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- Nll Loss: 0.7279 |
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- Log Odds Ratio: -0.3123 |
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- Log Odds Chosen: 1.0916 |
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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: 8e-06 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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- total_eval_batch_size: 4 |
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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: 5 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Nll Loss | Log Odds Ratio | Log Odds Chosen | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:| |
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| 4.0477 | 1.6 | 10 | 2.6148 | -0.1668 | -0.2037 | 0.8333 | 0.0369 | -2.0366 | -1.6676 | -0.5541 | -0.3265 | 2.5641 | -0.5002 | 0.4474 | |
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| 1.7128 | 3.2 | 20 | 1.3152 | -0.1092 | -0.1512 | 0.8333 | 0.0421 | -1.5124 | -1.0917 | -1.2255 | -0.9402 | 1.2267 | -0.4566 | 0.5915 | |
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| 0.9601 | 4.8 | 30 | 0.9698 | -0.0833 | -0.1380 | 1.0 | 0.0547 | -1.3800 | -0.8326 | -1.2364 | -0.9499 | 0.8983 | -0.3832 | 0.8390 | |
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| 0.7231 | 6.4 | 40 | 0.8362 | -0.0752 | -0.1390 | 1.0 | 0.0638 | -1.3898 | -0.7521 | -1.3672 | -1.0683 | 0.7749 | -0.3345 | 1.0067 | |
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| 0.6324 | 8.0 | 50 | 0.7904 | -0.0729 | -0.1410 | 1.0 | 0.0681 | -1.4101 | -0.7290 | -1.3658 | -1.0673 | 0.7331 | -0.3152 | 1.0809 | |
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| 0.6228 | 9.6 | 60 | 0.7838 | -0.0726 | -0.1414 | 1.0 | 0.0688 | -1.4145 | -0.7263 | -1.3572 | -1.0579 | 0.7279 | -0.3123 | 1.0916 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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