File size: 6,663 Bytes
2423fd5 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 |
---
license: apache-2.0
base_model: TheBloke/OpenHermes-2-Mistral-7B-GPTQ
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: mistral-dpo
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mistral-dpo
This model is a fine-tuned version of [TheBloke/OpenHermes-2-Mistral-7B-GPTQ](https://huggingface.co/TheBloke/OpenHermes-2-Mistral-7B-GPTQ) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7137
- Rewards/chosen: 1.0722
- Rewards/rejected: 0.8993
- Rewards/accuracies: 0.5962
- Rewards/margins: 0.1729
- Logps/rejected: -188.1420
- Logps/chosen: -180.8729
- Logits/rejected: -2.4148
- Logits/chosen: -2.4328
## 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: 0.0002
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- training_steps: 250
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.7053 | 0.0 | 10 | 0.6892 | 0.0818 | 0.0724 | 0.5962 | 0.0094 | -196.4110 | -190.7768 | -2.3946 | -2.4152 |
| 0.6805 | 0.0 | 20 | 0.6918 | -0.0354 | -0.0484 | 0.6346 | 0.0130 | -197.6190 | -191.9491 | -2.4006 | -2.4157 |
| 0.834 | 0.0 | 30 | 0.7086 | -0.2432 | -0.2641 | 0.5962 | 0.0210 | -199.7762 | -194.0263 | -2.4164 | -2.4252 |
| 0.8729 | 0.0 | 40 | 0.6981 | -0.1038 | -0.1416 | 0.6058 | 0.0377 | -198.5504 | -192.6330 | -2.4265 | -2.4351 |
| 0.838 | 0.0 | 50 | 0.6864 | 0.2782 | 0.2234 | 0.6058 | 0.0549 | -194.9011 | -188.8124 | -2.4238 | -2.4335 |
| 0.7253 | 0.0 | 60 | 0.6779 | 0.5564 | 0.4647 | 0.5865 | 0.0917 | -192.4881 | -186.0311 | -2.4271 | -2.4351 |
| 0.5718 | 0.01 | 70 | 0.6798 | 0.8872 | 0.7700 | 0.5769 | 0.1172 | -189.4352 | -182.7231 | -2.4266 | -2.4337 |
| 0.6437 | 0.01 | 80 | 0.6759 | 1.0681 | 0.9182 | 0.5096 | 0.1500 | -187.9532 | -180.9136 | -2.4499 | -2.4314 |
| 0.6098 | 0.01 | 90 | 0.7191 | 0.5345 | -0.0458 | 0.5577 | 0.5803 | -197.5928 | -186.2494 | -2.4888 | -2.4677 |
| 0.461 | 0.01 | 100 | 0.6948 | 1.0460 | 0.6785 | 0.5481 | 0.3675 | -190.3493 | -181.1343 | -2.4687 | -2.4447 |
| 1.0876 | 0.01 | 110 | 0.7081 | 1.0687 | 0.9388 | 0.5288 | 0.1299 | -187.7468 | -180.9077 | -2.4276 | -2.4196 |
| 0.5964 | 0.01 | 120 | 0.7045 | 0.9387 | 0.7995 | 0.5673 | 0.1391 | -189.1394 | -182.2079 | -2.4186 | -2.4276 |
| 0.6637 | 0.01 | 130 | 0.7018 | 0.9248 | 0.7781 | 0.5865 | 0.1466 | -189.3533 | -182.3472 | -2.4240 | -2.4395 |
| 0.5702 | 0.01 | 140 | 0.6985 | 0.8728 | 0.7128 | 0.6058 | 0.1600 | -190.0070 | -182.8667 | -2.4273 | -2.4452 |
| 0.8064 | 0.01 | 150 | 0.6941 | 0.8313 | 0.6588 | 0.6058 | 0.1725 | -190.5471 | -183.2818 | -2.4245 | -2.4424 |
| 0.7656 | 0.01 | 160 | 0.6877 | 0.7222 | 0.5277 | 0.5962 | 0.1945 | -191.8579 | -184.3729 | -2.4206 | -2.4390 |
| 0.6725 | 0.01 | 170 | 0.6949 | 0.8229 | 0.6362 | 0.5865 | 0.1867 | -190.7732 | -183.3658 | -2.4268 | -2.4442 |
| 0.6524 | 0.01 | 180 | 0.7100 | 0.9856 | 0.8195 | 0.5673 | 0.1660 | -188.9394 | -181.7392 | -2.4317 | -2.4486 |
| 1.0287 | 0.02 | 190 | 0.7161 | 1.0244 | 0.8611 | 0.5769 | 0.1634 | -188.5242 | -181.3504 | -2.4263 | -2.4431 |
| 0.8451 | 0.02 | 200 | 0.7186 | 1.0966 | 0.9354 | 0.5769 | 0.1613 | -187.7810 | -180.6283 | -2.4266 | -2.4435 |
| 0.6098 | 0.02 | 210 | 0.7159 | 1.1066 | 0.9427 | 0.5865 | 0.1639 | -187.7074 | -180.5288 | -2.4209 | -2.4382 |
| 0.5698 | 0.02 | 220 | 0.7149 | 1.1019 | 0.9356 | 0.5962 | 0.1663 | -187.7789 | -180.5757 | -2.4156 | -2.4336 |
| 0.7013 | 0.02 | 230 | 0.7145 | 1.0913 | 0.9216 | 0.5962 | 0.1697 | -187.9192 | -180.6817 | -2.4142 | -2.4319 |
| 2.6822 | 0.02 | 240 | 0.7143 | 1.0768 | 0.9049 | 0.5962 | 0.1720 | -188.0860 | -180.8263 | -2.4140 | -2.4322 |
| 0.9203 | 0.02 | 250 | 0.7137 | 1.0722 | 0.8993 | 0.5962 | 0.1729 | -188.1420 | -180.8729 | -2.4148 | -2.4328 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.1
|