zephyr-7b-gemma-dpo
This model is a fine-tuned version of HuggingFaceH4/zephyr-7b-gemma-sft-v0.1 on the argilla/dpo-mix-7k dataset. It achieves the following results on the evaluation set:
- Loss: 0.4658
- Rewards/chosen: -4.1134
- Rewards/rejected: -5.8777
- Rewards/accuracies: 0.7292
- Rewards/margins: 1.7644
- Logps/rejected: -479.6258
- Logps/chosen: -445.9359
- Logits/rejected: 85.7594
- Logits/chosen: 91.4868
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.1497 | 1.8957 | 100 | 0.4608 | -4.1286 | -5.8457 | 0.7292 | 1.7171 | -478.9854 | -446.2400 | 85.7808 | 91.4893 |
Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for fedyanin/zephyr-7b-gemma-dpo
Base model
google/gemma-7b
Finetuned
HuggingFaceH4/zephyr-7b-gemma-sft-v0.1