metadata
library_name: transformers
license: llama3.2
base_model: tanliboy/llama-3.2-3b-sft-2
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: llama-3.2-3b-dpo-2
results: []
llama-3.2-3b-dpo-2
This model is a fine-tuned version of tanliboy/llama-3.2-3b-sft-2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5808
- Rewards/chosen: 1.8125
- Rewards/rejected: -4.0822
- Rewards/accuracies: 0.7880
- Rewards/margins: 5.8947
- Logps/rejected: -387.3112
- Logps/chosen: -337.8669
- Logits/rejected: 0.2355
- Logits/chosen: 0.1785
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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- 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: 0.03
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.7596 | 0.1741 | 100 | 0.7588 | 0.1349 | -1.4398 | 0.6994 | 1.5747 | -360.8871 | -354.6434 | 0.6135 | 0.5482 |
| 0.6725 | 0.3483 | 200 | 0.6680 | 0.6247 | -2.7323 | 0.7278 | 3.3569 | -373.8118 | -349.7451 | 0.5335 | 0.4718 |
| 0.6452 | 0.5224 | 300 | 0.6514 | 0.1770 | -3.8036 | 0.75 | 3.9807 | -384.5256 | -354.2216 | 0.5477 | 0.4866 |
| 0.6259 | 0.6966 | 400 | 0.6328 | 0.9885 | -3.5382 | 0.7722 | 4.5267 | -381.8713 | -346.1070 | 0.4531 | 0.3927 |
| 0.5709 | 0.8707 | 500 | 0.6219 | 0.9150 | -4.0091 | 0.7816 | 4.9242 | -386.5804 | -346.8415 | 0.4148 | 0.3563 |
| 0.5835 | 1.0448 | 600 | 0.6094 | 1.5034 | -3.6390 | 0.7722 | 5.1423 | -382.8790 | -340.9584 | 0.3504 | 0.2933 |
| 0.5571 | 1.2190 | 700 | 0.5992 | 1.5696 | -3.7206 | 0.7690 | 5.2901 | -383.6949 | -340.2962 | 0.3217 | 0.2649 |
| 0.5532 | 1.3931 | 800 | 0.5954 | 1.7147 | -3.7261 | 0.7785 | 5.4408 | -383.7506 | -338.8453 | 0.2961 | 0.2383 |
| 0.5168 | 1.5673 | 900 | 0.5930 | 1.9934 | -3.3982 | 0.7753 | 5.3916 | -380.4709 | -336.0577 | 0.2838 | 0.2266 |
| 0.5232 | 1.7414 | 1000 | 0.5884 | 1.7308 | -4.0024 | 0.7816 | 5.7332 | -386.5127 | -338.6839 | 0.2787 | 0.2220 |
| 0.5574 | 1.9155 | 1100 | 0.5849 | 1.8420 | -3.9351 | 0.7911 | 5.7771 | -385.8401 | -337.5714 | 0.2706 | 0.2134 |
| 0.5077 | 2.0897 | 1200 | 0.5842 | 1.6188 | -4.2472 | 0.7880 | 5.8659 | -388.9607 | -339.8043 | 0.2657 | 0.2083 |
| 0.4952 | 2.2638 | 1300 | 0.5837 | 1.9316 | -3.8913 | 0.7816 | 5.8229 | -385.4018 | -336.6759 | 0.2694 | 0.2115 |
| 0.5236 | 2.4380 | 1400 | 0.5812 | 1.8289 | -4.0636 | 0.7880 | 5.8925 | -387.1253 | -337.7025 | 0.2465 | 0.1895 |
| 0.5001 | 2.6121 | 1500 | 0.5814 | 1.7432 | -4.1735 | 0.7848 | 5.9167 | -388.2242 | -338.5596 | 0.2395 | 0.1826 |
| 0.5246 | 2.7862 | 1600 | 0.5809 | 1.8622 | -4.0120 | 0.7880 | 5.8742 | -386.6093 | -337.3701 | 0.2395 | 0.1825 |
| 0.5042 | 2.9604 | 1700 | 0.5808 | 1.8125 | -4.0822 | 0.7880 | 5.8947 | -387.3112 | -337.8669 | 0.2355 | 0.1785 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1