---
library_name: peft
license: apache-2.0
base_model: unsloth/mistral-7b-v0.2
tags:
- axolotl
- generated_from_trainer
model-index:
- name: ebf49ab7-f89b-4e6a-b5b6-7c9f6466e27c
  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>

# ebf49ab7-f89b-4e6a-b5b6-7c9f6466e27c

This model is a fine-tuned version of [unsloth/mistral-7b-v0.2](https://huggingface.co/unsloth/mistral-7b-v0.2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8634

## 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: 110
- 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        | 0.0005 | 1    | 3.8445          |
| 2.9324        | 0.0271 | 50   | 3.0242          |
| 3.2723        | 0.0543 | 100  | 2.3571          |
| 3.0635        | 0.0814 | 150  | 2.0274          |
| 4.7947        | 0.1085 | 200  | 1.5986          |
| 2.3622        | 0.1356 | 250  | 1.5911          |
| 2.6259        | 0.1628 | 300  | 1.2451          |
| 1.6583        | 0.1899 | 350  | 1.1302          |
| 1.8973        | 0.2170 | 400  | 0.9359          |
| 1.8216        | 0.2442 | 450  | 0.8727          |
| 1.3534        | 0.2713 | 500  | 0.8634          |


### Framework versions

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