---
base_model: mistralai/Mistral-7B-v0.1
library_name: peft
license: apache-2.0
metrics:
- accuracy
tags:
- trl
- reward-trainer
- generated_from_trainer
model-index:
- name: pairwise-reward-zephyr-7b-sft-qlora-ultrafeedback-binarized-20240925-122042
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# pairwise-reward-zephyr-7b-sft-qlora-ultrafeedback-binarized-20240925-122042

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: 0.4788
- Accuracy: 0.7536

## 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: 1.5e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.6633        | 0.0526 | 100  | 0.6175          | 0.6929   |
| 0.6204        | 0.1052 | 200  | 0.5689          | 0.7255   |
| 0.5895        | 0.1578 | 300  | 0.5263          | 0.7341   |
| 0.5285        | 0.2104 | 400  | 0.5183          | 0.7431   |
| 0.4919        | 0.2630 | 500  | 0.5192          | 0.7356   |
| 0.5085        | 0.3155 | 600  | 0.5057          | 0.7531   |
| 0.5322        | 0.3681 | 700  | 0.5066          | 0.7486   |
| 0.4976        | 0.4207 | 800  | 0.4962          | 0.7561   |
| 0.549         | 0.4733 | 900  | 0.5012          | 0.7647   |
| 0.5175        | 0.5259 | 1000 | 0.4887          | 0.7587   |
| 0.4525        | 0.5785 | 1100 | 0.4980          | 0.7551   |
| 0.4847        | 0.6311 | 1200 | 0.4848          | 0.7516   |
| 0.5429        | 0.6837 | 1300 | 0.4878          | 0.7481   |
| 0.4348        | 0.7363 | 1400 | 0.4844          | 0.7551   |
| 0.4346        | 0.7889 | 1500 | 0.4848          | 0.7521   |
| 0.513         | 0.8414 | 1600 | 0.4837          | 0.7566   |
| 0.442         | 0.8940 | 1700 | 0.4814          | 0.7561   |
| 0.4531        | 0.9466 | 1800 | 0.4796          | 0.7607   |
| 0.4533        | 0.9992 | 1900 | 0.4788          | 0.7536   |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1