gemma-7b-dpo-full-mix1-beta-0.4-epoch-3
This model is a fine-tuned version of lewtun/gemma-7b-sft-full-deita-10k-v0 on the argilla/dpo-mix-7k dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3044
- Rewards/chosen: -6.0191
- Rewards/rejected: -11.1290
- Rewards/accuracies: 0.75
- Rewards/margins: 5.1099
- Logps/rejected: -479.3722
- Logps/chosen: -468.4523
- Logits/rejected: 98.8291
- Logits/chosen: 104.8679
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: 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 |
0.2569 |
1.9 |
100 |
1.0775 |
-6.7226 |
-12.3440 |
0.7396 |
5.6214 |
-482.4095 |
-470.2108 |
99.2330 |
105.2899 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.1