cira-7b-dpo-lora-merge
This model is a fine-tuned version of David-Xu/llama-2-7b-cira-sft-v0.1-merge on the David-Xu/astronomy-stack-dpo-20-percent dataset. It achieves the following results on the evaluation set:
- Loss: 0.6183
- Rewards/chosen: 0.5535
- Rewards/rejected: 0.3385
- Rewards/accuracies: 0.6784
- Rewards/margins: 0.2150
- Logps/rejected: -652.2422
- Logps/chosen: -795.1126
- Logits/rejected: -1.1812
- Logits/chosen: -1.0305
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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6618 | 0.11 | 100 | -0.8082 | -1.0029 | -823.6102 | -665.3923 | 0.6664 | 0.6432 | 0.2685 | 0.0615 | 0.2070 |
| 0.6079 | 0.22 | 200 | -1.0530 | -1.2188 | -794.3279 | -642.6389 | 0.6463 | 0.6508 | 0.5613 | 0.1268 | 0.4345 |
| 0.6029 | 0.33 | 300 | -1.0367 | -1.1965 | -793.2078 | -644.8513 | 0.6360 | 0.6558 | 0.5725 | 0.1601 | 0.4124 |
| 0.6123 | 0.45 | 400 | -1.1220 | -1.2658 | -787.7750 | -641.9633 | 0.6291 | 0.6608 | 0.6269 | 0.1856 | 0.4413 |
| 0.5596 | 0.56 | 500 | -1.0852 | -1.2330 | -790.7928 | -646.7930 | 0.6230 | 0.6683 | 0.5967 | 0.2037 | 0.3930 |
| 0.5382 | 0.67 | 600 | -1.0547 | -1.2034 | -793.2486 | -650.0926 | 0.6199 | 0.6709 | 0.5721 | 0.2121 | 0.3600 |
| 0.5952 | 0.78 | 700 | -1.0324 | -1.1827 | -794.9604 | -652.0420 | 0.6186 | 0.6784 | 0.5550 | 0.2145 | 0.3405 |
| 0.5792 | 0.89 | 800 | -1.0308 | -1.1812 | -795.125 | -652.2705 | 0.6182 | 0.6784 | 0.5534 | 0.2151 | 0.3382 |
Framework versions
- PEFT 0.9.0
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2