---
library_name: peft
license: apache-2.0
base_model: unsloth/Qwen2-7B
tags:
- axolotl
- generated_from_trainer
model-index:
- name: c8038877-817b-4835-97ac-6a49b034bc00
  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>

# c8038877-817b-4835-97ac-6a49b034bc00

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: 1.2725

## 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: 0.000215
- train_batch_size: 4
- eval_batch_size: 4
- seed: 150
- 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        | 0.0006 | 1    | 2.7593          |
| 1.0018        | 0.0288 | 50   | 1.4175          |
| 0.7892        | 0.0576 | 100  | 1.4868          |
| 0.8345        | 0.0864 | 150  | 1.5111          |
| 0.7475        | 0.1152 | 200  | 1.3708          |
| 0.7694        | 0.1441 | 250  | 1.3522          |
| 0.7995        | 0.1729 | 300  | 1.2939          |
| 0.7331        | 0.2017 | 350  | 1.2823          |
| 0.7806        | 0.2305 | 400  | 1.2758          |
| 0.7941        | 0.2593 | 450  | 1.2717          |
| 0.7293        | 0.2881 | 500  | 1.2725          |


### Framework versions

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