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---
license: apache-2.0
library_name: peft
tags:
- alignment-handbook
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- snorkelai/Snorkel-Mistral-PairRM-DPO-Dataset
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: zephyr-7b-dpo-qlora
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. -->
# zephyr-7b-dpo-qlora
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the snorkelai/Snorkel-Mistral-PairRM-DPO-Dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6668
- Rewards/chosen: -0.2672
- Rewards/rejected: -0.3491
- Rewards/accuracies: 0.6137
- Rewards/margins: 0.0819
- Logps/rejected: -378.9569
- Logps/chosen: -361.0521
- Logits/rejected: -2.5949
- Logits/chosen: -2.5884
## 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
- gradient_accumulation_steps: 4
- total_train_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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6933 | 0.08 | 100 | 0.6930 | -0.0077 | -0.0080 | 0.5177 | 0.0004 | -344.8478 | -335.0984 | -2.4838 | -2.4768 |
| 0.6926 | 0.16 | 200 | 0.6923 | -0.0138 | -0.0155 | 0.5427 | 0.0017 | -345.5920 | -335.7114 | -2.4836 | -2.4766 |
| 0.6906 | 0.24 | 300 | 0.6917 | -0.0130 | -0.0161 | 0.5523 | 0.0031 | -345.6560 | -335.6324 | -2.4879 | -2.4809 |
| 0.6884 | 0.32 | 400 | 0.6898 | -0.0075 | -0.0146 | 0.5807 | 0.0071 | -345.4990 | -335.0794 | -2.4972 | -2.4901 |
| 0.6753 | 0.4 | 500 | 0.6856 | -0.1385 | -0.1579 | 0.5630 | 0.0194 | -359.8317 | -348.1783 | -2.4986 | -2.4916 |
| 0.6839 | 0.48 | 600 | 0.6815 | -0.3188 | -0.3556 | 0.5667 | 0.0368 | -379.6049 | -366.2155 | -2.5394 | -2.5333 |
| 0.6535 | 0.56 | 700 | 0.6770 | -0.4204 | -0.4741 | 0.5763 | 0.0537 | -391.4496 | -376.3719 | -2.5483 | -2.5425 |
| 0.6764 | 0.64 | 800 | 0.6724 | -0.2481 | -0.3087 | 0.5990 | 0.0606 | -374.9128 | -359.1413 | -2.5714 | -2.5651 |
| 0.6753 | 0.72 | 900 | 0.6704 | -0.4283 | -0.5062 | 0.5983 | 0.0780 | -394.6671 | -377.1592 | -2.5807 | -2.5750 |
| 0.6459 | 0.8 | 1000 | 0.6680 | -0.2406 | -0.3163 | 0.6127 | 0.0757 | -375.6733 | -358.3894 | -2.5924 | -2.5858 |
| 0.6541 | 0.88 | 1100 | 0.6670 | -0.2806 | -0.3625 | 0.6157 | 0.0820 | -380.2968 | -362.3882 | -2.5942 | -2.5878 |
| 0.6422 | 0.96 | 1200 | 0.6669 | -0.2657 | -0.3473 | 0.6157 | 0.0817 | -378.7738 | -360.8972 | -2.5963 | -2.5898 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.0 |