---
library_name: peft
license: apache-2.0
base_model: unsloth/Qwen2-7B
tags:
- axolotl
- generated_from_trainer
model-index:
- name: a916de6c-4265-47da-aa5b-d3cfbfa791bc
  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>

# a916de6c-4265-47da-aa5b-d3cfbfa791bc

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: 1.0719

## 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: 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        | 0.0007 | 1    | 1.3709          |
| 2.2737        | 0.0349 | 50   | 1.2990          |
| 2.3175        | 0.0698 | 100  | 1.2746          |
| 2.1608        | 0.1047 | 150  | 1.2196          |
| 1.9825        | 0.1397 | 200  | 1.1976          |
| 2.2834        | 0.1746 | 250  | 1.1505          |
| 1.9559        | 0.2095 | 300  | 1.1187          |
| 2.2902        | 0.2444 | 350  | 1.0975          |
| 2.3402        | 0.2793 | 400  | 1.0797          |
| 2.3676        | 0.3142 | 450  | 1.0727          |
| 2.1411        | 0.3492 | 500  | 1.0719          |


### Framework versions

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