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---
base_model: mistralai/Mistral-7B-v0.1
library_name: peft
license: apache-2.0
tags:
- trl
- dpo
- generated_from_trainer
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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4952
- Rewards/chosen: -2.8107
- Rewards/rejected: -3.8708
- Rewards/accuracies: 0.7718
- Rewards/margins: 1.0601
- Logps/rejected: -631.7385
- Logps/chosen: -545.9743
- Logits/rejected: -1.0385
- Logits/chosen: -1.1509
## 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: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 32
- 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 | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected |
|:-------------:|:------:|:----:|:-------------:|:---------------:|:------------:|:--------------:|:---------------:|:------------------:|:--------------:|:---------------:|:----------------:|
| 0.6163 | 0.1047 | 100 | -2.1006 | -2.0162 | -303.8351 | -310.3097 | 0.6178 | 0.6806 | -0.3893 | 0.2672 | -0.6565 |
| 0.5679 | 0.2094 | 200 | -1.8227 | -1.7394 | -352.2879 | -389.6575 | 0.5567 | 0.7401 | -0.8739 | 0.5761 | -1.4500 |
| 0.5412 | 0.3141 | 300 | -1.3111 | -1.2181 | -421.3257 | -483.0423 | 0.5305 | 0.7460 | -1.5642 | 0.8196 | -2.3838 |
| 0.5364 | 0.4187 | 400 | -1.2334 | -1.1332 | -416.6979 | -476.3458 | 0.5143 | 0.7579 | -1.5180 | 0.7989 | -2.3169 |
| 0.5046 | 0.5234 | 500 | -1.1373 | -1.0302 | -529.9542 | -605.2977 | 0.5062 | 0.7579 | -2.6505 | 0.9559 | -3.6064 |
| 0.4736 | 0.6281 | 600 | 0.5059 | -2.7244 | -3.7650 | 0.7639 | 1.0406 | -621.1549 | -537.3406 | -1.0135 | -1.1253 |
| 0.4619 | 0.7328 | 700 | 0.4994 | -2.9240 | -3.9991 | 0.7619 | 1.0750 | -644.5651 | -557.3041 | -1.0064 | -1.1194 |
| 0.4926 | 0.8375 | 800 | 0.4962 | -2.7247 | -3.7455 | 0.7659 | 1.0207 | -619.2051 | -537.3770 | -1.0516 | -1.1641 |
| 0.4856 | 0.9422 | 900 | 0.4952 | -2.8107 | -3.8708 | 0.7718 | 1.0601 | -631.7385 | -545.9743 | -1.0385 | -1.1509 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1 |