gemma-7b-borpo
This model is a fine-tuned version of google/gemma-7b on the argilla/dpo-mix-7k dataset. It achieves the following results on the evaluation set:
- Loss: 1.5984
- Rewards/chosen: -0.0575
- Rewards/rejected: -0.0699
- Rewards/accuracies: 0.5899
- Rewards/margins: 0.0124
- Logps/rejected: -1.3977
- Logps/chosen: -1.1506
- Logits/rejected: 270.9628
- Logits/chosen: 299.8625
- Nll Loss: 1.5312
- Log Odds Ratio: -0.6761
- Log Odds Chosen: 0.3679
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: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: inverse_sqrt
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Nll Loss | Log Odds Ratio | Log Odds Chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.4516 | 0.9968 | 157 | 1.4765 | -0.0513 | -0.0577 | 0.5468 | 0.0064 | -1.1547 | -1.0260 | 293.8872 | 321.9495 | 1.4282 | -0.6924 | 0.1911 |
| 1.0587 | 2.0 | 315 | 1.4250 | -0.0502 | -0.0595 | 0.5468 | 0.0093 | -1.1904 | -1.0035 | 296.0850 | 323.6012 | 1.3729 | -0.6901 | 0.2723 |
| 0.5897 | 2.9905 | 471 | 1.5984 | -0.0575 | -0.0699 | 0.5899 | 0.0124 | -1.3977 | -1.1506 | 270.9628 | 299.8625 | 1.5312 | -0.6761 | 0.3679 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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Base model
google/gemma-7b