metadata
base_model: argsearch/llama-7b-sft-float32
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- Dahoas/full-hh-rlhf
model-index:
- name: llama-7b-sft-DPO
results: []
llama-7b-sft-DPO
This model is a fine-tuned version of argsearch/llama-7b-sft-float32 on the Dahoas/full-hh-rlhf dataset. It achieves the following results on the evaluation set:
- Loss: 0.6525
- Rewards/chosen: 0.3315
- Rewards/rejected: 0.1953
- Rewards/accuracies: 0.6080
- Rewards/margins: 0.1362
- Logps/rejected: -633.3815
- Logps/chosen: -690.5654
- Logits/rejected: -1.9212
- Logits/chosen: -1.9766
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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6884 | 0.06 | 100 | 0.6886 | 0.0879 | 0.0774 | 0.5647 | 0.0105 | -645.1731 | -714.9250 | -2.7786 | -2.8754 |
| 0.6769 | 0.11 | 200 | 0.6809 | 0.2546 | 0.2194 | 0.5747 | 0.0352 | -630.9728 | -698.2556 | -2.6094 | -2.6971 |
| 0.6734 | 0.17 | 300 | 0.6755 | 0.2980 | 0.2471 | 0.5833 | 0.0508 | -628.1946 | -693.9142 | -2.5226 | -2.6062 |
| 0.6684 | 0.23 | 400 | 0.6713 | 0.3480 | 0.2822 | 0.5888 | 0.0658 | -624.6848 | -688.9108 | -2.4007 | -2.4782 |
| 0.6647 | 0.29 | 500 | 0.6671 | 0.3495 | 0.2706 | 0.6048 | 0.0789 | -625.8477 | -688.7593 | -2.3026 | -2.3749 |
| 0.6598 | 0.34 | 600 | 0.6636 | 0.3311 | 0.2429 | 0.6058 | 0.0882 | -628.6143 | -690.6030 | -2.1694 | -2.2345 |
| 0.6598 | 0.4 | 700 | 0.6606 | 0.2824 | 0.1853 | 0.6106 | 0.0971 | -634.3779 | -695.4718 | -1.9252 | -1.9781 |
| 0.6563 | 0.46 | 800 | 0.6585 | 0.3476 | 0.2374 | 0.6071 | 0.1102 | -629.1707 | -688.9521 | -2.0030 | -2.0599 |
| 0.6636 | 0.51 | 900 | 0.6572 | 0.3569 | 0.2427 | 0.6119 | 0.1142 | -628.6379 | -688.0209 | -1.9872 | -2.0440 |
| 0.6436 | 0.57 | 1000 | 0.6558 | 0.2921 | 0.1732 | 0.6096 | 0.1190 | -635.5912 | -694.4999 | -1.9618 | -2.0181 |
| 0.6759 | 0.63 | 1100 | 0.6548 | 0.3436 | 0.2165 | 0.6071 | 0.1272 | -631.2626 | -689.3489 | -1.9627 | -2.0198 |
| 0.6679 | 0.69 | 1200 | 0.6542 | 0.3533 | 0.2212 | 0.6077 | 0.1321 | -630.7878 | -688.3820 | -1.9058 | -1.9598 |
| 0.6358 | 0.74 | 1300 | 0.6533 | 0.3363 | 0.2036 | 0.6074 | 0.1327 | -632.5449 | -690.0779 | -1.9447 | -2.0015 |
| 0.6473 | 0.8 | 1400 | 0.6528 | 0.3378 | 0.2021 | 0.6080 | 0.1357 | -632.6981 | -689.9300 | -1.9072 | -1.9621 |
| 0.6447 | 0.86 | 1500 | 0.6526 | 0.3221 | 0.1869 | 0.6080 | 0.1352 | -634.2156 | -691.5005 | -1.9226 | -1.9781 |
| 0.6546 | 0.91 | 1600 | 0.6525 | 0.3303 | 0.1941 | 0.6074 | 0.1362 | -633.5018 | -690.6824 | -1.9134 | -1.9684 |
| 0.6725 | 0.97 | 1700 | 0.6525 | 0.3312 | 0.1950 | 0.6074 | 0.1363 | -633.4115 | -690.5892 | -1.9098 | -1.9645 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2