---
library_name: peft
license: apache-2.0
base_model: unsloth/Qwen2-7B
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 22e4f64e-ce84-44bc-ae90-1c695e284b96
  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>

# 22e4f64e-ce84-44bc-ae90-1c695e284b96

This model is a fine-tuned version of [unsloth/Qwen2-7B](https://huggingface.co/unsloth/Qwen2-7B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3219

## 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: 0.000202
- 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        | 0.0004 | 1    | 2.6280          |
| 1.3739        | 0.0184 | 50   | 1.5840          |
| 1.3833        | 0.0368 | 100  | 1.4967          |
| 1.3041        | 0.0552 | 150  | 1.4766          |
| 1.2805        | 0.0736 | 200  | 1.4655          |
| 1.2476        | 0.0920 | 250  | 1.4171          |
| 1.2002        | 0.1104 | 300  | 1.3866          |
| 1.24          | 0.1287 | 350  | 1.3594          |
| 1.2489        | 0.1471 | 400  | 1.3325          |
| 1.2365        | 0.1655 | 450  | 1.3238          |
| 1.2489        | 0.1839 | 500  | 1.3219          |


### Framework versions

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