metadata
license: mit
base_model: HuggingFaceH4/mistral-7b-sft-beta
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: zephyr-7b-dpo-full
results: []
zephyr-7b-dpo-full
This model is a fine-tuned version of HuggingFaceH4/mistral-7b-sft-beta on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5440
- Rewards/chosen: -2.2940
- Rewards/rejected: -3.0054
- Rewards/accuracies: 0.7090
- Rewards/margins: 0.7114
- Logps/rejected: -451.6765
- Logps/chosen: -373.9785
- Logits/rejected: 0.3244
- Logits/chosen: 0.0742
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: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 64
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6789 | 0.08 | 100 | 0.6770 | -0.1062 | -0.1422 | 0.5914 | 0.0360 | -165.3552 | -155.1927 | -2.7255 | -2.7337 |
| 0.6062 | 0.16 | 200 | 0.6079 | -1.0212 | -1.3873 | 0.6670 | 0.3660 | -289.8622 | -246.6971 | -2.3696 | -2.3856 |
| 0.5965 | 0.24 | 300 | 0.5907 | -1.3779 | -1.8008 | 0.6623 | 0.4229 | -331.2100 | -282.3621 | -2.2450 | -2.2656 |
| 0.5729 | 0.32 | 400 | 0.5711 | -1.6763 | -2.2404 | 0.6828 | 0.5640 | -375.1720 | -312.2064 | -1.2920 | -1.3760 |
| 0.5645 | 0.4 | 500 | 0.5639 | -2.0721 | -2.6869 | 0.6987 | 0.6147 | -419.8194 | -351.7883 | -0.6091 | -0.7860 |
| 0.5513 | 0.48 | 600 | 0.5582 | -2.9237 | -3.5389 | 0.7108 | 0.6152 | -505.0223 | -436.9386 | 0.1224 | -0.1054 |
| 0.5571 | 0.56 | 700 | 0.5559 | -2.7971 | -3.5456 | 0.7043 | 0.7485 | -505.6961 | -424.2823 | 0.2980 | 0.0356 |
| 0.5609 | 0.64 | 800 | 0.5469 | -2.4314 | -3.0831 | 0.7108 | 0.6517 | -459.4439 | -387.7092 | 0.1922 | -0.0312 |
| 0.5514 | 0.72 | 900 | 0.5474 | -2.4774 | -3.2082 | 0.6996 | 0.7308 | -471.9533 | -392.3096 | 0.5382 | 0.2860 |
| 0.527 | 0.8 | 1000 | 0.5454 | -2.5040 | -3.2071 | 0.7080 | 0.7031 | -471.8454 | -394.9711 | 0.6372 | 0.3871 |
| 0.5487 | 0.88 | 1100 | 0.5444 | -2.2851 | -2.9963 | 0.7090 | 0.7112 | -450.7599 | -373.0831 | 0.4336 | 0.1858 |
| 0.5483 | 0.96 | 1200 | 0.5440 | -2.2940 | -3.0054 | 0.7090 | 0.7114 | -451.6765 | -373.9785 | 0.3244 | 0.0742 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1