---
base_model: unsloth/Qwen2-7B
library_name: peft
license: apache-2.0
tags:
- unsloth
- generated_from_trainer
model-index:
- name: Qwen2-7B_magiccoder_default
  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. -->

# Qwen2-7B_magiccoder_default

This model is a fine-tuned version of [unsloth/Qwen2-7B](https://huggingface.co./unsloth/Qwen2-7B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9894

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.02
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8215        | 0.0261 | 4    | 0.9220          |
| 0.9247        | 0.0522 | 8    | 0.9780          |
| 0.9611        | 0.0783 | 12   | 0.9693          |
| 0.9392        | 0.1044 | 16   | 0.9867          |
| 1.0135        | 0.1305 | 20   | 1.0108          |
| 0.9152        | 0.1566 | 24   | 1.0167          |
| 0.9298        | 0.1827 | 28   | 1.0251          |
| 1.0625        | 0.2088 | 32   | 1.0349          |
| 0.9695        | 0.2349 | 36   | 1.0332          |
| 1.0104        | 0.2610 | 40   | 1.0390          |
| 1.0721        | 0.2871 | 44   | 1.0406          |
| 1.0397        | 0.3132 | 48   | 1.0449          |
| 0.9623        | 0.3393 | 52   | 1.0448          |
| 0.9735        | 0.3654 | 56   | 1.0436          |
| 1.0016        | 0.3915 | 60   | 1.0431          |
| 1.0557        | 0.4176 | 64   | 1.0401          |
| 1.0377        | 0.4437 | 68   | 1.0373          |
| 1.0022        | 0.4698 | 72   | 1.0361          |
| 1.0193        | 0.4959 | 76   | 1.0328          |
| 0.9806        | 0.5220 | 80   | 1.0301          |
| 1.0542        | 0.5481 | 84   | 1.0263          |
| 0.9692        | 0.5742 | 88   | 1.0244          |
| 1.0464        | 0.6003 | 92   | 1.0215          |
| 0.9771        | 0.6264 | 96   | 1.0166          |
| 1.0659        | 0.6525 | 100  | 1.0146          |
| 0.9476        | 0.6786 | 104  | 1.0106          |
| 0.983         | 0.7047 | 108  | 1.0074          |
| 0.9585        | 0.7308 | 112  | 1.0035          |
| 0.9193        | 0.7569 | 116  | 0.9997          |
| 0.9041        | 0.7830 | 120  | 0.9975          |
| 0.9697        | 0.8091 | 124  | 0.9954          |
| 0.9464        | 0.8352 | 128  | 0.9933          |
| 1.0252        | 0.8613 | 132  | 0.9917          |
| 0.9665        | 0.8874 | 136  | 0.9909          |
| 0.9948        | 0.9135 | 140  | 0.9904          |
| 0.946         | 0.9396 | 144  | 0.9897          |
| 1.0095        | 0.9657 | 148  | 0.9896          |
| 0.9675        | 0.9918 | 152  | 0.9894          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1