---
library_name: peft
license: apache-2.0
base_model: unsloth/Qwen2-7B-Instruct
tags:
- axolotl
- generated_from_trainer
model-index:
- name: f1343a55-ea5b-4ee5-b0fa-aee22cd64ed5
  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>

# f1343a55-ea5b-4ee5-b0fa-aee22cd64ed5

This model is a fine-tuned version of [unsloth/Qwen2-7B-Instruct](https://huggingface.co/unsloth/Qwen2-7B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1320

## 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        | 0.0011 | 1    | 2.6140          |
| 0.465         | 0.0544 | 50   | 0.5987          |
| 0.4137        | 0.1088 | 100  | 0.5497          |
| 0.2994        | 0.1631 | 150  | 0.4509          |
| 0.3535        | 0.2175 | 200  | 0.2948          |
| 0.203         | 0.2719 | 250  | 0.2723          |
| 0.4967        | 0.3263 | 300  | 0.2410          |
| 0.232         | 0.3806 | 350  | 0.2100          |
| 0.1905        | 0.4350 | 400  | 0.1442          |
| 0.2123        | 0.4894 | 450  | 0.1319          |
| 0.2352        | 0.5438 | 500  | 0.1320          |


### Framework versions

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