---
license: apache-2.0
library_name: peft
tags:
- unsloth
- generated_from_trainer
base_model: Qwen/Qwen2-7B
model-index:
- name: qwen2_Magiccoder_evol_10k
  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_Magiccoder_evol_10k

This model is a fine-tuned version of [Qwen/Qwen2-7B](https://huggingface.co/Qwen/Qwen2-7B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7725

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.02
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8717        | 0.0261 | 4    | 0.8953          |
| 0.8201        | 0.0522 | 8    | 0.8217          |
| 0.7952        | 0.0783 | 12   | 0.8046          |
| 0.7488        | 0.1044 | 16   | 0.7901          |
| 0.8162        | 0.1306 | 20   | 0.7853          |
| 0.6904        | 0.1567 | 24   | 0.7835          |
| 0.6959        | 0.1828 | 28   | 0.7821          |
| 0.8719        | 0.2089 | 32   | 0.7817          |
| 0.7546        | 0.2350 | 36   | 0.7795          |
| 0.7769        | 0.2611 | 40   | 0.7773          |
| 0.838         | 0.2872 | 44   | 0.7758          |
| 0.8043        | 0.3133 | 48   | 0.7745          |
| 0.7233        | 0.3395 | 52   | 0.7741          |
| 0.699         | 0.3656 | 56   | 0.7737          |
| 0.728         | 0.3917 | 60   | 0.7731          |
| 0.7698        | 0.4178 | 64   | 0.7734          |
| 0.8031        | 0.4439 | 68   | 0.7734          |
| 0.7362        | 0.4700 | 72   | 0.7731          |
| 0.7598        | 0.4961 | 76   | 0.7728          |
| 0.7305        | 0.5222 | 80   | 0.7727          |
| 0.8435        | 0.5483 | 84   | 0.7726          |
| 0.7321        | 0.5745 | 88   | 0.7726          |
| 0.8194        | 0.6006 | 92   | 0.7726          |
| 0.7417        | 0.6267 | 96   | 0.7728          |
| 0.8314        | 0.6528 | 100  | 0.7726          |
| 0.711         | 0.6789 | 104  | 0.7726          |
| 0.7745        | 0.7050 | 108  | 0.7725          |
| 0.744         | 0.7311 | 112  | 0.7724          |
| 0.7047        | 0.7572 | 116  | 0.7725          |
| 0.6911        | 0.7834 | 120  | 0.7724          |
| 0.7593        | 0.8095 | 124  | 0.7725          |
| 0.6959        | 0.8356 | 128  | 0.7725          |
| 0.8262        | 0.8617 | 132  | 0.7723          |
| 0.7802        | 0.8878 | 136  | 0.7724          |
| 0.7966        | 0.9139 | 140  | 0.7724          |
| 0.7511        | 0.9400 | 144  | 0.7723          |
| 0.8079        | 0.9661 | 148  | 0.7724          |
| 0.7663        | 0.9922 | 152  | 0.7725          |


### Framework versions

- PEFT 0.7.1
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1