---
library_name: peft
license: apache-2.0
base_model: unsloth/mistral-7b-instruct-v0.2
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 9c2ddf3e-356e-4e6e-835b-77f42c23e2db
  results: []
---

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[<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>

# 9c2ddf3e-356e-4e6e-835b-77f42c23e2db

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: 1.9130

## 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: 0.000218
- train_batch_size: 4
- eval_batch_size: 4
- seed: 180
- 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    | 2.3282          |
| 4.0091        | 0.0030 | 50   | 2.0920          |
| 4.0166        | 0.0060 | 100  | 2.1335          |
| 4.0742        | 0.0089 | 150  | 2.1239          |
| 3.9373        | 0.0119 | 200  | 2.0794          |
| 4.0466        | 0.0149 | 250  | 2.0389          |
| 3.9251        | 0.0179 | 300  | 1.9936          |
| 3.9635        | 0.0208 | 350  | 1.9587          |
| 3.9004        | 0.0238 | 400  | 1.9290          |
| 3.8992        | 0.0268 | 450  | 1.9156          |
| 3.7904        | 0.0298 | 500  | 1.9130          |


### Framework versions

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