metadata
license: other
library_name: peft
tags:
- llama-factory
- lora
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B
model-index:
- name: sft_trained_woaqa_llama3_dpo
results: []
sft_trained_woaqa_llama3_dpo
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the sft_wo_aqa_pref dataset. It achieves the following results on the evaluation set:
- Loss: 2.0569
- Rewards/chosen: 9.0148
- Rewards/rejected: 7.8220
- Rewards/accuracies: 0.6667
- Rewards/margins: 1.1928
- Logps/rejected: -180.5298
- Logps/chosen: -151.5047
- Logits/rejected: -1.4439
- Logits/chosen: -1.4397
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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.3287 | 0.33 | 200 | 1.8699 | 9.9343 | 9.1282 | 0.6312 | 0.8061 | -167.4677 | -142.3102 | -1.1863 | -1.1862 |
| 1.1821 | 0.67 | 400 | 1.9729 | 9.9379 | 9.2024 | 0.6113 | 0.7354 | -166.7256 | -142.2745 | -1.2732 | -1.2718 |
| 0.9116 | 1.0 | 600 | 1.9455 | 9.7997 | 8.9466 | 0.6482 | 0.8531 | -169.2835 | -143.6562 | -1.3527 | -1.3510 |
| 0.8412 | 1.33 | 800 | 2.0041 | 9.5449 | 8.5167 | 0.6397 | 1.0282 | -173.5831 | -146.2043 | -1.4206 | -1.4179 |
| 0.7345 | 1.67 | 1000 | 2.0659 | 9.1494 | 8.1514 | 0.6426 | 0.9980 | -177.2357 | -150.1593 | -1.4325 | -1.4290 |
| 0.6609 | 2.0 | 1200 | 2.0321 | 9.0327 | 7.8126 | 0.6681 | 1.2200 | -180.6237 | -151.3265 | -1.4359 | -1.4321 |
| 0.6768 | 2.33 | 1400 | 2.0313 | 9.1007 | 7.8929 | 0.6709 | 1.2079 | -179.8211 | -150.6457 | -1.4472 | -1.4432 |
| 0.615 | 2.67 | 1600 | 2.0515 | 9.0972 | 7.9582 | 0.6624 | 1.1390 | -179.1680 | -150.6812 | -1.4413 | -1.4370 |
Framework versions
- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2