Gemma-7B-It-ORPO-SALT-HALF
This model is a fine-tuned version of google/gemma-7b-it on the dpo_mix_en and the bct_non_cot_dpo_500 datasets. It achieves the following results on the evaluation set:
- Loss: 1.3159
- Rewards/chosen: -0.1249
- Rewards/rejected: -0.1471
- Rewards/accuracies: 0.5619
- Rewards/margins: 0.0222
- Logps/rejected: -1.4709
- Logps/chosen: -1.2488
- Logits/rejected: 253.8645
- Logits/chosen: 253.5439
- Sft Loss: 1.2488
- Odds Ratio Loss: 0.6713
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1.422 | 0.8467 | 500 | 1.3896 | -0.1322 | -0.1546 | 0.5752 | 0.0224 | -1.5459 | -1.3222 | 250.5634 | 250.2739 | 1.3222 | 0.6733 |
1.3103 | 1.6935 | 1000 | 1.3313 | -0.1264 | -0.1489 | 0.5695 | 0.0224 | -1.4886 | -1.2642 | 253.1350 | 252.8147 | 1.2642 | 0.6718 |
1.2057 | 2.5402 | 1500 | 1.3159 | -0.1249 | -0.1471 | 0.5619 | 0.0222 | -1.4709 | -1.2488 | 253.8645 | 253.5439 | 1.2488 | 0.6713 |
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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