zephyr-7b-dpo-qlora
This model is a fine-tuned version of ale-bay/zephyr-7b-sft-qlora on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.4975
- Rewards/chosen: -2.4549
- Rewards/rejected: -3.4757
- Rewards/accuracies: 0.7490
- Rewards/margins: 1.0207
- Logps/rejected: -595.2866
- Logps/chosen: -517.1966
- Logits/rejected: -1.3432
- Logits/chosen: -1.4358
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-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 16
- 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 | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6641 | 0.05 | 100 | 0.6636 | 0.0054 | -0.0681 | 0.6900 | 0.0735 | -254.5337 | -271.1659 | -2.0436 | -2.1368 |
| 0.6105 | 0.1 | 200 | 0.6075 | -0.3236 | -0.5938 | 0.6890 | 0.2702 | -307.0967 | -304.0613 | -2.0030 | -2.0919 |
| 0.5883 | 0.16 | 300 | 0.5817 | -0.7122 | -1.1286 | 0.7020 | 0.4164 | -360.5768 | -342.9188 | -1.9914 | -2.0761 |
| 0.5651 | 0.21 | 400 | 0.5665 | -0.7901 | -1.2897 | 0.7250 | 0.4996 | -376.6874 | -350.7093 | -1.9001 | -1.9820 |
| 0.5136 | 0.26 | 500 | 0.5520 | -1.0330 | -1.6646 | 0.7190 | 0.6316 | -414.1808 | -374.9992 | -1.8081 | -1.8880 |
| 0.5587 | 0.31 | 600 | 0.5327 | -1.3215 | -2.0089 | 0.7320 | 0.6874 | -448.6079 | -403.8534 | -1.4665 | -1.5609 |
| 0.5167 | 0.37 | 700 | 0.5299 | -1.2797 | -2.1992 | 0.7230 | 0.9196 | -467.6413 | -399.6684 | -1.3918 | -1.4903 |
| 0.5465 | 0.42 | 800 | 0.5189 | -1.6646 | -2.4686 | 0.7200 | 0.8041 | -494.5844 | -438.1617 | -1.3685 | -1.4642 |
| 0.5002 | 0.47 | 900 | 0.5142 | -1.7844 | -2.7217 | 0.7290 | 0.9373 | -519.8885 | -450.1383 | -1.4179 | -1.5054 |
| 0.5017 | 0.52 | 1000 | 0.5058 | -2.6175 | -3.6120 | 0.7360 | 0.9946 | -608.9218 | -533.4493 | -1.2973 | -1.3948 |
| 0.4966 | 0.58 | 1100 | 0.5043 | -2.0581 | -2.9819 | 0.7370 | 0.9239 | -545.9103 | -477.5080 | -1.3783 | -1.4740 |
| 0.5087 | 0.63 | 1200 | 0.5040 | -2.3715 | -3.3475 | 0.7450 | 0.9760 | -582.4712 | -508.8495 | -1.3331 | -1.4262 |
| 0.4799 | 0.68 | 1300 | 0.5011 | -2.3067 | -3.3444 | 0.7450 | 1.0377 | -582.1562 | -502.3687 | -1.3340 | -1.4277 |
| 0.4606 | 0.73 | 1400 | 0.4991 | -2.5016 | -3.5583 | 0.7430 | 1.0567 | -603.5469 | -521.8631 | -1.3291 | -1.4219 |
| 0.4763 | 0.79 | 1500 | 0.4985 | -2.4979 | -3.5204 | 0.7470 | 1.0225 | -599.7631 | -521.4944 | -1.3394 | -1.4325 |
| 0.5008 | 0.84 | 1600 | 0.4977 | -2.4555 | -3.4719 | 0.7480 | 1.0164 | -594.9102 | -517.2504 | -1.3492 | -1.4415 |
| 0.4654 | 0.89 | 1700 | 0.4976 | -2.4498 | -3.4672 | 0.7510 | 1.0174 | -594.4417 | -516.6852 | -1.3478 | -1.4402 |
| 0.4854 | 0.94 | 1800 | 0.4975 | -2.4526 | -3.4731 | 0.7480 | 1.0205 | -595.0339 | -516.9640 | -1.3441 | -1.4366 |
| 0.4879 | 0.99 | 1900 | 0.4974 | -2.4531 | -3.4740 | 0.75 | 1.0209 | -595.1221 | -517.0148 | -1.3432 | -1.4359 |
Framework versions
- PEFT 0.7.1
- Transformers 4.39.3
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.15.2
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Model tree for ale-bay/zephyr-7b-dpo-qlora
Base model
mistralai/Mistral-7B-v0.1