metadata
license: apache-2.0
library_name: peft
tags:
- trl
- dpo
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: zephyr-7b-dpo-qlora
results: []
zephyr-7b-dpo-qlora
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4921
- Rewards/chosen: -2.5098
- Rewards/rejected: -3.5900
- Rewards/accuracies: 0.7550
- Rewards/margins: 1.0803
- Logps/rejected: -600.2638
- Logps/chosen: -516.2831
- Logits/rejected: 2.5098
- Logits/chosen: 2.2971
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-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 16
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6622 | 0.05 | 100 | 0.6637 | 0.0126 | -0.0636 | 0.6840 | 0.0762 | -247.6176 | -264.0424 | -2.2973 | -2.3242 |
| 0.6069 | 0.1 | 200 | 0.6175 | -0.5399 | -0.8086 | 0.6720 | 0.2687 | -322.1209 | -319.2918 | -1.9985 | -2.0644 |
| 0.5858 | 0.16 | 300 | 0.5707 | -0.8385 | -1.3622 | 0.6930 | 0.5238 | -377.4863 | -349.1537 | 0.2196 | 0.1195 |
| 0.5518 | 0.21 | 400 | 0.5536 | -0.8070 | -1.4119 | 0.7230 | 0.6049 | -382.4471 | -346.0015 | 0.8423 | 0.7208 |
| 0.5953 | 0.26 | 500 | 0.5575 | -0.6678 | -1.1831 | 0.7110 | 0.5153 | -359.5695 | -332.0846 | 1.2558 | 1.0708 |
| 0.5032 | 0.31 | 600 | 0.5359 | -1.3551 | -2.1333 | 0.7310 | 0.7782 | -454.5939 | -400.8145 | 2.8427 | 2.7062 |
| 0.5741 | 0.37 | 700 | 0.5317 | -1.2904 | -2.0407 | 0.7260 | 0.7503 | -445.3269 | -394.3451 | 3.1371 | 2.9904 |
| 0.5318 | 0.42 | 800 | 0.5149 | -1.6058 | -2.4688 | 0.7450 | 0.8630 | -488.1442 | -425.8877 | 3.7140 | 3.5383 |
| 0.5353 | 0.47 | 900 | 0.5125 | -2.5710 | -3.5411 | 0.7460 | 0.9701 | -595.3752 | -522.4096 | 4.4179 | 4.2065 |
| 0.574 | 0.52 | 1000 | 0.5035 | -2.6228 | -3.6684 | 0.7370 | 1.0456 | -608.1039 | -527.5898 | 2.6517 | 2.4408 |
| 0.471 | 0.58 | 1100 | 0.5028 | -2.6309 | -3.7142 | 0.75 | 1.0833 | -612.6806 | -528.3990 | 2.2637 | 2.0694 |
| 0.4888 | 0.63 | 1200 | 0.4965 | -2.4412 | -3.4135 | 0.7530 | 0.9723 | -582.6143 | -509.4261 | 2.4042 | 2.2263 |
| 0.5204 | 0.68 | 1300 | 0.4941 | -2.2701 | -3.2940 | 0.7480 | 1.0239 | -570.6591 | -492.3148 | 2.2065 | 2.0121 |
| 0.5158 | 0.73 | 1400 | 0.4925 | -2.6194 | -3.7070 | 0.7540 | 1.0875 | -611.9571 | -527.2493 | 2.4817 | 2.2784 |
| 0.4677 | 0.79 | 1500 | 0.4922 | -2.6220 | -3.7128 | 0.7540 | 1.0908 | -612.5421 | -527.5074 | 2.5848 | 2.3739 |
| 0.5464 | 0.84 | 1600 | 0.4925 | -2.5137 | -3.5972 | 0.7510 | 1.0835 | -600.9805 | -516.6763 | 2.4955 | 2.2803 |
| 0.5078 | 0.89 | 1700 | 0.4920 | -2.5031 | -3.5840 | 0.7550 | 1.0809 | -599.6627 | -515.6122 | 2.5160 | 2.3031 |
| 0.4864 | 0.94 | 1800 | 0.4921 | -2.5103 | -3.5902 | 0.7550 | 1.0799 | -600.2827 | -516.3320 | 2.5115 | 2.2982 |
| 0.5211 | 0.99 | 1900 | 0.4921 | -2.5098 | -3.5900 | 0.7550 | 1.0803 | -600.2638 | -516.2831 | 2.5098 | 2.2971 |
Framework versions
- PEFT 0.7.1
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2