| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: alignment-handbook/zephyr-7b-sft-full |
| tags: |
| - alignment-handbook |
| - trl |
| - dpo |
| - generated_from_trainer |
| - trl |
| - dpo |
| - alignment-handbook |
| - generated_from_trainer |
| datasets: |
| - HuggingFaceH4/ultrafeedback_binarized |
| model-index: |
| - name: zephyr-7b-align-scan |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # zephyr-7b-align-scan |
|
|
| This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) on the HuggingFaceH4/ultrafeedback_binarized dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5960 |
| - Rewards/chosen: -0.6252 |
| - Rewards/rejected: -1.0907 |
| - Rewards/accuracies: 0.3690 |
| - Rewards/margins: 0.4655 |
| - Logps/rejected: -190.1945 |
| - Logps/chosen: -137.0085 |
| - Logits/rejected: 0.9319 |
| - Logits/chosen: 0.4522 |
| |
| ## Model description |
| |
| More information needed |
| |
| ## Intended uses & limitations |
| |
| More information needed |
| |
| ## Training and evaluation data |
| |
| More information needed |
| |
| ## Training procedure |
| |
| ### Training hyperparameters |
| |
| The following hyperparameters were used during training: |
| - learning_rate: 5e-07 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - distributed_type: multi-GPU |
| - num_devices: 4 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 64 |
| - total_eval_batch_size: 32 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 1 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected | |
| |:-------------:|:------:|:----:|:-------------:|:---------------:|:------------:|:--------------:|:---------------:|:------------------:|:--------------:|:---------------:|:----------------:| |
| | 0.6719 | 0.1047 | 100 | -2.3487 | -2.3310 | -73.2865 | -85.4479 | 0.6687 | 0.3274 | 0.0120 | 0.0552 | -0.0432 | |
| | 0.6488 | 0.2093 | 200 | -1.2584 | -1.2396 | -102.5743 | -130.3725 | 0.6348 | 0.3373 | -0.2808 | 0.2116 | -0.4924 | |
| | 0.6331 | 0.3140 | 300 | -1.1873 | -1.0320 | -120.1307 | -157.0977 | 0.6195 | 0.3452 | -0.4564 | 0.3033 | -0.7597 | |
| | 0.6321 | 0.4186 | 400 | 0.0335 | 0.3728 | -146.9637 | -190.2757 | 0.6099 | 0.3631 | -0.7247 | 0.3667 | -1.0915 | |
| | 0.6318 | 0.5233 | 500 | 2.6547 | 2.9545 | -155.4930 | -204.6371 | 0.6105 | 0.3552 | -0.8100 | 0.4251 | -1.2351 | |
| | 0.5978 | 0.6279 | 600 | 0.9606 | 1.4420 | -147.8560 | -199.5121 | 0.6015 | 0.3591 | -0.7336 | 0.4502 | -1.1838 | |
| | 0.6113 | 0.7326 | 700 | 1.1833 | 1.7188 | -150.6854 | -204.9195 | 0.5986 | 0.3651 | -0.7619 | 0.4760 | -1.2379 | |
| | 0.5885 | 0.8373 | 800 | 0.5613 | 1.0128 | -141.6925 | -192.4845 | 0.5974 | 0.3690 | -0.6720 | 0.4415 | -1.1136 | |
| | 0.595 | 0.9419 | 900 | 0.4326 | 0.9106 | -136.2882 | -189.5506 | 0.5958 | 0.3710 | -0.6180 | 0.4663 | -1.0842 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.44.2 |
| - Pytorch 2.4.0 |
| - Datasets 2.21.0 |
| - Tokenizers 0.19.1 |
|
|
