---
base_model: unsloth/Qwen2-7B
library_name: peft
license: apache-2.0
tags:
- unsloth
- generated_from_trainer
model-index:
- name: Qwen2-7B_magiccoder_reverse
  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_reverse

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: 0.9869

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.8213        | 0.0261 | 4    | 0.9216          |
| 0.9106        | 0.0522 | 8    | 0.9644          |
| 0.9506        | 0.0783 | 12   | 0.9631          |
| 0.9339        | 0.1044 | 16   | 0.9845          |
| 1.0039        | 0.1305 | 20   | 0.9997          |
| 0.9095        | 0.1566 | 24   | 1.0116          |
| 0.9241        | 0.1827 | 28   | 1.0198          |
| 1.0582        | 0.2088 | 32   | 1.0291          |
| 0.9677        | 0.2349 | 36   | 1.0307          |
| 1.0044        | 0.2610 | 40   | 1.0355          |
| 1.0672        | 0.2871 | 44   | 1.0388          |
| 1.0368        | 0.3132 | 48   | 1.0402          |
| 0.9603        | 0.3393 | 52   | 1.0420          |
| 0.9709        | 0.3654 | 56   | 1.0398          |
| 1.0019        | 0.3915 | 60   | 1.0403          |
| 1.0537        | 0.4176 | 64   | 1.0384          |
| 1.0365        | 0.4437 | 68   | 1.0345          |
| 1.0           | 0.4698 | 72   | 1.0332          |
| 1.0165        | 0.4959 | 76   | 1.0306          |
| 0.9778        | 0.5220 | 80   | 1.0271          |
| 1.0497        | 0.5481 | 84   | 1.0229          |
| 0.9652        | 0.5742 | 88   | 1.0203          |
| 1.0435        | 0.6003 | 92   | 1.0185          |
| 0.9769        | 0.6264 | 96   | 1.0141          |
| 1.0648        | 0.6525 | 100  | 1.0104          |
| 0.9463        | 0.6786 | 104  | 1.0079          |
| 0.9835        | 0.7047 | 108  | 1.0049          |
| 0.9584        | 0.7308 | 112  | 1.0010          |
| 0.9185        | 0.7569 | 116  | 0.9973          |
| 0.9021        | 0.7830 | 120  | 0.9950          |
| 0.9684        | 0.8091 | 124  | 0.9930          |
| 0.9461        | 0.8352 | 128  | 0.9913          |
| 1.0232        | 0.8613 | 132  | 0.9895          |
| 0.9646        | 0.8874 | 136  | 0.9885          |
| 0.9912        | 0.9135 | 140  | 0.9874          |
| 0.9464        | 0.9396 | 144  | 0.9870          |
| 1.0104        | 0.9657 | 148  | 0.9868          |
| 0.9624        | 0.9918 | 152  | 0.9869          |


### Framework versions

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