Gemma-7B-It-ORPO
This model is a fine-tuned version of google/gemma-7b-it on the dpo_mix_en dataset. It achieves the following results on the evaluation set:
- Loss: 1.3471
- Rewards/chosen: -0.1281
- Rewards/rejected: -0.1500
- Rewards/accuracies: 0.5610
- Rewards/margins: 0.0219
- Logps/rejected: -1.5004
- Logps/chosen: -1.2814
- Logits/rejected: 254.6614
- Logits/chosen: 254.4679
- Sft Loss: 1.2814
- Odds Ratio Loss: 0.6571
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-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 3.0
Training results
Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Sft Loss | Odds Ratio Loss |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1.5041 | 0.8891 | 500 | 1.4185 | -0.1352 | -0.1564 | 0.5530 | 0.0212 | -1.5644 | -1.3522 | 250.7549 | 250.6463 | 1.3522 | 0.6626 |
1.428 | 1.7782 | 1000 | 1.3595 | -0.1294 | -0.1509 | 0.5600 | 0.0215 | -1.5091 | -1.2937 | 254.1350 | 253.9581 | 1.2937 | 0.6586 |
1.3302 | 2.6673 | 1500 | 1.3471 | -0.1281 | -0.1500 | 0.5610 | 0.0219 | -1.5004 | -1.2814 | 254.6614 | 254.4679 | 1.2814 | 0.6571 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1
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