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--- |
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license: apache-2.0 |
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base_model: mistralai/Mistral-7B-v0.1 |
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tags: |
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- alignment-handbook |
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- trl |
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- orpo |
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- generated_from_trainer |
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- trl |
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- orpo |
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- alignment-handbook |
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- generated_from_trainer |
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datasets: |
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- HuggingFaceH4/ultrafeedback_binarized |
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model-index: |
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- name: zephyr-7b-sft-full-orpo |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/statking/huggingface/runs/90a8kp39) |
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# zephyr-7b-sft-full-orpo |
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the HuggingFaceH4/ultrafeedback_binarized dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4701 |
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- Rewards/chosen: -0.0364 |
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- Rewards/rejected: -0.0499 |
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- Rewards/accuracies: 0.6587 |
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- Rewards/margins: 0.0135 |
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- Logps/rejected: -0.9978 |
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- Logps/chosen: -0.7282 |
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- Logits/rejected: -2.9263 |
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- Logits/chosen: -2.9434 |
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- Nll Loss: 0.4357 |
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- Log Odds Ratio: -0.6093 |
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- Log Odds Chosen: 0.4456 |
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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: 7e-06 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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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: inverse_sqrt |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 1 |
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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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| 0.5226 | 0.1049 | 100 | 0.5280 | -0.0386 | -0.0472 | 0.6329 | 0.0086 | -0.9448 | -0.7728 | -2.7583 | -2.7860 | 0.4953 | -0.6326 | 0.2873 | |
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| 0.5074 | 0.2098 | 200 | 0.5134 | -0.0381 | -0.0478 | 0.6409 | 0.0098 | -0.9566 | -0.7612 | -2.6736 | -2.7002 | 0.4774 | -0.6357 | 0.3190 | |
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| 0.5265 | 0.3146 | 300 | 0.5012 | -0.0379 | -0.0479 | 0.6329 | 0.0099 | -0.9572 | -0.7588 | -2.7317 | -2.7594 | 0.4653 | -0.6374 | 0.3278 | |
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| 0.5194 | 0.4195 | 400 | 0.4912 | -0.0371 | -0.0478 | 0.6429 | 0.0107 | -0.9559 | -0.7417 | -2.6640 | -2.6974 | 0.4560 | -0.6284 | 0.3607 | |
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| 0.5008 | 0.5244 | 500 | 0.4847 | -0.0373 | -0.0489 | 0.6508 | 0.0117 | -0.9786 | -0.7455 | -2.5957 | -2.6294 | 0.4499 | -0.6209 | 0.3873 | |
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| 0.4725 | 0.6293 | 600 | 0.4794 | -0.0362 | -0.0470 | 0.6349 | 0.0107 | -0.9394 | -0.7248 | -2.6147 | -2.6477 | 0.4435 | -0.6320 | 0.3567 | |
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| 0.4875 | 0.7341 | 700 | 0.4767 | -0.0368 | -0.0498 | 0.6409 | 0.0129 | -0.9955 | -0.7365 | -2.6910 | -2.7213 | 0.4416 | -0.6158 | 0.4180 | |
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| 0.4796 | 0.8390 | 800 | 0.4740 | -0.0371 | -0.0508 | 0.6508 | 0.0137 | -1.0162 | -0.7416 | -2.7913 | -2.8114 | 0.4396 | -0.6169 | 0.4363 | |
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| 0.4851 | 0.9439 | 900 | 0.4714 | -0.0357 | -0.0466 | 0.6528 | 0.0109 | -0.9324 | -0.7143 | -2.9543 | -2.9692 | 0.4361 | -0.6245 | 0.3669 | |
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### Framework versions |
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- Transformers 4.41.0.dev0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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