metadata
license: apache-2.0
base_model: TheBloke/OpenHermes-2-Mistral-7B-GPTQ
tags:
- generated_from_trainer
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: 0.6751
- Rewards/chosen: 0.0215
- Rewards/rejected: -0.0002
- Rewards/accuracies: 0.4375
- Rewards/margins: 0.0217
- Logps/rejected: -132.4150
- Logps/chosen: -333.1984
- Logits/rejected: -2.7074
- Logits/chosen: -2.3899
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: 200
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.7508 | 0.01 | 10 | 0.7479 | -0.3566 | -0.2195 | 0.25 | -0.1371 | -351.7834 | -711.3196 | -1.6251 | -1.4448 |
| 0.982 | 0.01 | 20 | 0.7765 | -0.5130 | -0.3405 | 0.25 | -0.1726 | -472.7075 | -867.7224 | -1.1628 | -1.0511 |
| 0.6985 | 0.01 | 30 | 0.6899 | 0.0062 | 0.0027 | 0.375 | 0.0036 | -129.5716 | -348.4551 | -2.7357 | -2.3605 |
| 0.6959 | 0.02 | 40 | 0.6935 | 0.0008 | 0.0022 | 0.25 | -0.0014 | -130.0675 | -353.8832 | -2.7275 | -2.3561 |
| 0.6944 | 0.03 | 50 | 0.6892 | 0.0073 | 0.0040 | 0.4375 | 0.0033 | -128.2573 | -347.3910 | -2.7124 | -2.3589 |
| 0.7785 | 0.03 | 60 | 0.7361 | -0.4130 | -0.2866 | 0.375 | -0.1264 | -418.8091 | -767.6629 | -1.3320 | -1.2310 |
| 0.7009 | 0.04 | 70 | 0.7892 | -0.5637 | -0.3765 | 0.3125 | -0.1872 | -508.7737 | -918.3933 | -1.1171 | -1.0132 |
| 0.7886 | 0.04 | 80 | 0.7862 | -0.5738 | -0.3892 | 0.3125 | -0.1845 | -521.4880 | -928.4485 | -1.1127 | -1.0064 |
| 0.7059 | 0.04 | 90 | 0.7127 | -0.0370 | -0.0108 | 0.4375 | -0.0263 | -143.0086 | -391.7115 | -2.6542 | -2.3045 |
| 0.6793 | 0.05 | 100 | 0.6981 | -0.0357 | -0.0284 | 0.375 | -0.0073 | -160.6859 | -390.4216 | -2.5199 | -2.2133 |
| 0.7085 | 0.06 | 110 | 0.7039 | -0.0251 | -0.0089 | 0.3125 | -0.0162 | -141.1216 | -379.7617 | -2.6806 | -2.3312 |
| 0.6959 | 0.06 | 120 | 0.6974 | -0.0162 | -0.0077 | 0.375 | -0.0085 | -139.9174 | -370.8595 | -2.6925 | -2.3406 |
| 0.6897 | 0.07 | 130 | 0.6948 | -0.0122 | -0.0069 | 0.3125 | -0.0053 | -139.1202 | -366.9146 | -2.6971 | -2.3477 |
| 0.6897 | 0.07 | 140 | 0.6935 | -0.0104 | -0.0067 | 0.3125 | -0.0038 | -138.8917 | -365.1371 | -2.6948 | -2.3576 |
| 0.7015 | 0.07 | 150 | 0.6864 | 0.0011 | -0.0042 | 0.4375 | 0.0054 | -136.4684 | -353.5512 | -2.6973 | -2.3710 |
| 0.6497 | 0.08 | 160 | 0.6814 | 0.0099 | -0.0023 | 0.4375 | 0.0122 | -134.5819 | -344.8182 | -2.7048 | -2.3806 |
| 0.6893 | 0.09 | 170 | 0.6787 | 0.0147 | -0.0015 | 0.4375 | 0.0161 | -133.7108 | -340.0247 | -2.7106 | -2.3874 |
| 0.7002 | 0.09 | 180 | 0.6776 | 0.0168 | -0.0010 | 0.4375 | 0.0178 | -133.2137 | -337.8709 | -2.7120 | -2.3888 |
| 0.6875 | 0.1 | 190 | 0.6755 | 0.0209 | -0.0002 | 0.4375 | 0.0211 | -132.4327 | -333.8066 | -2.7093 | -2.3902 |
| 0.6781 | 0.1 | 200 | 0.6751 | 0.0215 | -0.0002 | 0.4375 | 0.0217 | -132.4150 | -333.1984 | -2.7074 | -2.3899 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0