metadata
license: mit
base_model: databricks/dolly-v2-7b
tags:
- generated_from_trainer
model-index:
- name: dolly-v2-7b-dpo-full-1-epoch-hydrox-safe
results: []
dolly-v2-7b-dpo-full-1-epoch-hydrox-safe
This model is a fine-tuned version of databricks/dolly-v2-7b on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0371
- Rewards/chosen: 4.2799
- Rewards/rejected: -3.8888
- Rewards/accuracies: 0.9857
- Rewards/margins: 8.1686
- Logps/rejected: -598.4040
- Logps/chosen: -377.1240
- Logits/rejected: -1.2002
- Logits/chosen: -1.5171
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: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- 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: linear
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.618 | 0.03 | 100 | 0.5642 | 0.6988 | -0.1139 | 0.7424 | 0.8127 | -560.6550 | -412.9344 | -1.1894 | -1.4878 |
| 0.3539 | 0.07 | 200 | 0.3197 | 1.9159 | -0.2730 | 0.8847 | 2.1889 | -562.2463 | -400.7641 | -1.1625 | -1.4800 |
| 0.2287 | 0.1 | 300 | 0.2128 | 2.8057 | -0.5539 | 0.9200 | 3.3596 | -565.0551 | -391.8654 | -1.1361 | -1.4649 |
| 0.158 | 0.14 | 400 | 0.1673 | 3.4556 | -1.0339 | 0.9327 | 4.4895 | -569.8558 | -385.3670 | -1.1300 | -1.4622 |
| 0.1599 | 0.17 | 500 | 0.1397 | 3.7485 | -1.3338 | 0.9461 | 5.0823 | -572.8546 | -382.4376 | -1.1275 | -1.4607 |
| 0.1389 | 0.2 | 600 | 0.1273 | 3.9259 | -1.5111 | 0.9529 | 5.4371 | -574.6277 | -380.6633 | -1.1194 | -1.4519 |
| 0.0778 | 0.24 | 700 | 0.1122 | 4.0699 | -1.8498 | 0.9613 | 5.9197 | -578.0140 | -379.2233 | -1.1302 | -1.4542 |
| 0.0993 | 0.27 | 800 | 0.0975 | 4.2423 | -1.9934 | 0.9663 | 6.2357 | -579.4506 | -377.5001 | -1.1424 | -1.4689 |
| 0.111 | 0.31 | 900 | 0.0907 | 4.3218 | -2.2534 | 0.9697 | 6.5752 | -582.0501 | -376.7048 | -1.1542 | -1.4820 |
| 0.0893 | 0.34 | 1000 | 0.0882 | 4.3878 | -2.2588 | 0.9663 | 6.6466 | -582.1047 | -376.0451 | -1.1497 | -1.4694 |
| 0.079 | 0.37 | 1100 | 0.0840 | 4.4706 | -2.3132 | 0.9689 | 6.7838 | -582.6481 | -375.2164 | -1.1532 | -1.4807 |
| 0.0706 | 0.41 | 1200 | 0.0721 | 4.4319 | -2.6505 | 0.9722 | 7.0824 | -586.0217 | -375.6038 | -1.1667 | -1.4885 |
| 0.0705 | 0.44 | 1300 | 0.0725 | 4.3743 | -2.8717 | 0.9739 | 7.2460 | -588.2330 | -376.1799 | -1.1817 | -1.5001 |
| 0.0537 | 0.48 | 1400 | 0.0648 | 4.3847 | -2.9676 | 0.9756 | 7.3523 | -589.1927 | -376.0760 | -1.1789 | -1.5019 |
| 0.0483 | 0.51 | 1500 | 0.0604 | 4.3761 | -3.2295 | 0.9798 | 7.6056 | -591.8114 | -376.1613 | -1.1923 | -1.5114 |
| 0.0572 | 0.54 | 1600 | 0.0581 | 4.3258 | -3.2641 | 0.9773 | 7.5899 | -592.1575 | -376.6645 | -1.1855 | -1.5042 |
| 0.066 | 0.58 | 1700 | 0.0539 | 4.3270 | -3.3813 | 0.9815 | 7.7083 | -593.3289 | -376.6523 | -1.1886 | -1.5110 |
| 0.0561 | 0.61 | 1800 | 0.0501 | 4.3859 | -3.3980 | 0.9798 | 7.7839 | -593.4964 | -376.0636 | -1.1948 | -1.5144 |
| 0.0538 | 0.65 | 1900 | 0.0504 | 4.4209 | -3.4478 | 0.9815 | 7.8687 | -593.9944 | -375.7137 | -1.2036 | -1.5147 |
| 0.0493 | 0.68 | 2000 | 0.0472 | 4.3835 | -3.5804 | 0.9832 | 7.9639 | -595.3203 | -376.0873 | -1.1925 | -1.5071 |
| 0.0374 | 0.71 | 2100 | 0.0449 | 4.2972 | -3.7998 | 0.9840 | 8.0970 | -597.5147 | -376.9510 | -1.2020 | -1.5166 |
| 0.0475 | 0.75 | 2200 | 0.0442 | 4.3073 | -3.6486 | 0.9840 | 7.9559 | -596.0024 | -376.8494 | -1.1992 | -1.5177 |
| 0.0407 | 0.78 | 2300 | 0.0408 | 4.3011 | -3.7981 | 0.9882 | 8.0992 | -597.4978 | -376.9122 | -1.2078 | -1.5242 |
| 0.0386 | 0.82 | 2400 | 0.0397 | 4.3423 | -3.7314 | 0.9882 | 8.0737 | -596.8302 | -376.4996 | -1.2029 | -1.5133 |
| 0.0504 | 0.85 | 2500 | 0.0390 | 4.3732 | -3.7690 | 0.9857 | 8.1422 | -597.2065 | -376.1912 | -1.2024 | -1.5188 |
| 0.0402 | 0.88 | 2600 | 0.0377 | 4.3358 | -3.8299 | 0.9865 | 8.1656 | -597.8150 | -376.5649 | -1.1977 | -1.5158 |
| 0.038 | 0.92 | 2700 | 0.0397 | 4.3284 | -3.8383 | 0.9891 | 8.1667 | -597.8990 | -376.6386 | -1.2033 | -1.5139 |
| 0.0527 | 0.95 | 2800 | 0.0383 | 4.2985 | -3.8490 | 0.9857 | 8.1475 | -598.0059 | -376.9374 | -1.2037 | -1.5196 |
| 0.0365 | 0.99 | 2900 | 0.0379 | 4.3086 | -3.8349 | 0.9874 | 8.1435 | -597.8653 | -376.8369 | -1.1997 | -1.5156 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.1+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1