metadata
license: apache-2.0
library_name: peft
tags:
- trl
- dpo
- generated_from_trainer
base_model: TheBloke/OpenHermes-2-Mistral-7B-GPTQ
model-index:
- name: openhermes-mistral-dpo-gptq
results: []
openhermes-mistral-dpo-gptq
This model is a fine-tuned version of TheBloke/OpenHermes-2-Mistral-7B-GPTQ on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4346
- Rewards/chosen: 0.6886
- Rewards/rejected: -0.1517
- Rewards/accuracies: 0.875
- Rewards/margins: 0.8403
- Logps/rejected: -258.0681
- Logps/chosen: -269.4644
- Logits/rejected: -2.3873
- Logits/chosen: -2.4450
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- training_steps: 100
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6927 | 0.02 | 5 | 0.6723 | -0.0624 | -0.1130 | 0.5 | 0.0506 | -257.6814 | -276.9746 | -2.3921 | -2.4532 |
| 0.6896 | 0.04 | 10 | 0.6814 | -0.0837 | -0.1949 | 0.5625 | 0.1113 | -258.5006 | -277.1875 | -2.3785 | -2.4393 |
| 0.7286 | 0.06 | 15 | 0.7217 | -0.1116 | -0.2049 | 0.8125 | 0.0933 | -258.6005 | -277.4668 | -2.3732 | -2.4343 |
| 0.6049 | 0.08 | 20 | 0.6488 | -0.5231 | -0.7234 | 0.9375 | 0.2003 | -263.7849 | -281.5815 | -2.3599 | -2.4201 |
| 3.1019 | 0.1 | 25 | 0.6202 | -0.7269 | -1.0069 | 0.9375 | 0.2800 | -266.6205 | -283.6199 | -2.3529 | -2.4132 |
| 3.4522 | 0.12 | 30 | 0.6238 | -0.8793 | -1.2160 | 0.875 | 0.3367 | -268.7114 | -285.1440 | -2.3418 | -2.4001 |
| 1.7538 | 0.14 | 35 | 0.6336 | -0.5977 | -0.8794 | 0.875 | 0.2816 | -265.3451 | -282.3282 | -2.3479 | -2.4068 |
| 0.6167 | 0.16 | 40 | 0.6979 | 0.0308 | -0.1700 | 0.8125 | 0.2008 | -258.2513 | -276.0429 | -2.3591 | -2.4196 |
| 1.5103 | 0.18 | 45 | 0.7053 | 0.0521 | -0.1713 | 0.875 | 0.2233 | -258.2638 | -275.8300 | -2.3607 | -2.4207 |
| 0.6762 | 0.2 | 50 | 0.7144 | 0.1606 | -0.1470 | 0.875 | 0.3076 | -258.0209 | -274.7448 | -2.3658 | -2.4243 |
| 0.6587 | 0.22 | 55 | 0.7123 | 0.1399 | -0.2934 | 0.8125 | 0.4333 | -259.4854 | -274.9521 | -2.3670 | -2.4244 |
| 0.7563 | 0.24 | 60 | 0.7987 | 0.4547 | 0.0155 | 0.8125 | 0.4391 | -256.3959 | -271.8042 | -2.3793 | -2.4378 |
| 0.8208 | 0.26 | 65 | 0.8288 | 1.0234 | 0.5622 | 0.8125 | 0.4611 | -250.9289 | -266.1172 | -2.4012 | -2.4618 |
| 0.9904 | 0.28 | 70 | 0.7683 | 1.4763 | 0.9615 | 0.8125 | 0.5148 | -246.9362 | -261.5881 | -2.4184 | -2.4798 |
| 0.8327 | 0.3 | 75 | 0.6556 | 1.6107 | 1.0087 | 0.8125 | 0.6019 | -246.4639 | -260.2441 | -2.4218 | -2.4838 |
| 0.8238 | 0.32 | 80 | 0.5524 | 1.5571 | 0.8762 | 0.8125 | 0.6809 | -247.7892 | -260.7801 | -2.4168 | -2.4797 |
| 0.7712 | 0.34 | 85 | 0.5144 | 1.3444 | 0.6352 | 0.8125 | 0.7092 | -250.1996 | -262.9072 | -2.4079 | -2.4697 |
| 0.691 | 0.36 | 90 | 0.4688 | 1.0225 | 0.2544 | 0.875 | 0.7682 | -254.0075 | -266.1254 | -2.3981 | -2.4588 |
| 0.6386 | 0.38 | 95 | 0.4490 | 0.8498 | 0.0425 | 0.875 | 0.8074 | -256.1265 | -267.8524 | -2.3927 | -2.4521 |
| 0.6413 | 0.4 | 100 | 0.4346 | 0.6886 | -0.1517 | 0.875 | 0.8403 | -258.0681 | -269.4644 | -2.3873 | -2.4450 |
Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.0.1+cu117
- Datasets 2.17.1
- Tokenizers 0.15.2