---
library_name: peft
license: apache-2.0
base_model: unsloth/mistral-7b-instruct-v0.2
tags:
- axolotl
- generated_from_trainer
model-index:
- name: d0672be5-fbe8-4d5b-a644-9013deb8820c
  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. -->

[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<br>

# d0672be5-fbe8-4d5b-a644-9013deb8820c

This model is a fine-tuned version of [unsloth/mistral-7b-instruct-v0.2](https://huggingface.co/unsloth/mistral-7b-instruct-v0.2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1059

## 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: 0.000211
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- training_steps: 500

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0001 | 1    | 1.5842          |
| 2.2242        | 0.0035 | 50   | 1.1996          |
| 1.932         | 0.0071 | 100  | 1.2317          |
| 2.3692        | 0.0106 | 150  | 1.2062          |
| 2.0542        | 0.0141 | 200  | 1.1977          |
| 2.1478        | 0.0177 | 250  | 1.1813          |
| 1.9           | 0.0212 | 300  | 1.1527          |
| 1.778         | 0.0248 | 350  | 1.1319          |
| 1.9175        | 0.0283 | 400  | 1.1162          |
| 1.7999        | 0.0318 | 450  | 1.1087          |
| 1.6523        | 0.0354 | 500  | 1.1059          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1