Gemma-7B-It-ORPO-SALT
This model is a fine-tuned version of google/gemma-7b-it on the dpo_mix_en and the bct_non_cot_dpo_1000 datasets. It achieves the following results on the evaluation set:
- Loss: 1.2657
- Rewards/chosen: -0.1198
- Rewards/rejected: -0.1438
- Rewards/accuracies: 0.5700
- Rewards/margins: 0.0239
- Logps/rejected: -1.4377
- Logps/chosen: -1.1983
- Logits/rejected: 253.9599
- Logits/chosen: 253.6037
- Sft Loss: 1.1983
- Odds Ratio Loss: 0.6746
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1.374 | 0.8082 | 500 | 1.3436 | -0.1276 | -0.1503 | 0.5673 | 0.0227 | -1.5033 | -1.2762 | 249.9064 | 249.6123 | 1.2762 | 0.6738 |
1.1628 | 1.6165 | 1000 | 1.2833 | -0.1215 | -0.1446 | 0.5618 | 0.0231 | -1.4461 | -1.2153 | 253.1810 | 252.8272 | 1.2153 | 0.6796 |
1.1874 | 2.4247 | 1500 | 1.2657 | -0.1198 | -0.1438 | 0.5700 | 0.0239 | -1.4377 | -1.1983 | 253.9599 | 253.6037 | 1.1983 | 0.6746 |
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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