zephyr-7b-gemma-dpo
This model is a fine-tuned version of google/gemma-7b on the argilla/dpo-mix-7k dataset. It achieves the following results on the evaluation set:
- Loss: 0.8036
- Rewards/chosen: -0.4463
- Rewards/rejected: -1.2861
- Rewards/accuracies: 0.7292
- Rewards/margins: 0.8397
- Logps/rejected: -1648.0323
- Logps/chosen: -1530.0571
- Logits/rejected: -25.1620
- Logits/chosen: -18.0449
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: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- 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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.4114 | 1.8957 | 100 | 0.8002 | -0.4660 | -1.3128 | 0.7604 | 0.8468 | -1648.5675 | -1530.4515 | -25.1625 | -18.0007 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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