zephyr-7b-gemma-hinge
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: 0.5273
- Rewards/chosen: -2.6335
- Rewards/rejected: -3.8935
- Rewards/accuracies: 0.7292
- Rewards/margins: 1.2600
- Logps/rejected: -439.9419
- Logps/chosen: -416.3391
- Logits/rejected: 96.0524
- Logits/chosen: 101.8806
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.1516 | 1.8957 | 100 | 0.5250 | -2.6386 | -3.9001 | 0.7188 | 1.2616 | -440.0739 | -416.4398 | 95.9739 | 101.8169 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.1.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for chrlu/zephyr-7b-gemma-hinge
Base model
google/gemma-7b
Finetuned
HuggingFaceH4/zephyr-7b-gemma-sft-v0.1