zephyr-7b-dpo-full
This model is a fine-tuned version of lewtun/zephyr-7b-sft-full on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4949
- Rewards/chosen: -1.0109
- Rewards/rejected: -1.9949
- Rewards/accuracies: 0.7891
- Rewards/margins: 0.9840
- Logps/rejected: -458.5204
- Logps/chosen: -380.6149
- Logits/rejected: 1.7815
- Logits/chosen: 0.4467
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 | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected |
---|---|---|---|---|---|---|---|---|---|---|---|
0.5594 | 0.21 | 100 | -0.4568 | 0.0349 | -345.0751 | -391.4898 | 0.5459 | 0.7695 | -0.6555 | 0.6691 | -1.3246 |
0.5342 | 0.42 | 200 | 0.1644 | 1.0433 | -360.3595 | -414.7491 | 0.5221 | 0.8047 | -0.8084 | 0.7489 | -1.5572 |
0.5085 | 0.63 | 300 | 0.6383 | 1.9502 | -383.1190 | -455.6415 | 0.5045 | 0.7891 | -1.0360 | 0.9302 | -1.9662 |
0.4998 | 0.84 | 400 | 0.4907 | 1.8212 | -384.5488 | -461.4449 | 0.4953 | 0.7930 | -1.0503 | 0.9739 | -2.0242 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0
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