---
license: apache-2.0
library_name: peft
tags:
- unsloth
- generated_from_trainer
base_model: Qwen/Qwen2-7B
model-index:
- name: qwen2_Magiccoder_evol_10k_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_Magiccoder_evol_10k_reverse

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: 0.8272

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 32
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.8303        | 0.0261 | 4    | 0.8571          |
| 0.8267        | 0.0522 | 8    | 0.8449          |
| 0.8201        | 0.0784 | 12   | 0.8389          |
| 0.8002        | 0.1045 | 16   | 0.8436          |
| 0.8491        | 0.1306 | 20   | 0.8414          |
| 0.7448        | 0.1567 | 24   | 0.8434          |
| 0.7606        | 0.1828 | 28   | 0.8459          |
| 0.9214        | 0.2089 | 32   | 0.8474          |
| 0.8071        | 0.2351 | 36   | 0.8466          |
| 0.8353        | 0.2612 | 40   | 0.8479          |
| 0.8762        | 0.2873 | 44   | 0.8473          |
| 0.8544        | 0.3134 | 48   | 0.8475          |
| 0.7855        | 0.3395 | 52   | 0.8482          |
| 0.7725        | 0.3656 | 56   | 0.8467          |
| 0.8044        | 0.3918 | 60   | 0.8470          |
| 0.8282        | 0.4179 | 64   | 0.8446          |
| 0.853         | 0.4440 | 68   | 0.8449          |
| 0.8047        | 0.4701 | 72   | 0.8439          |
| 0.8145        | 0.4962 | 76   | 0.8431          |
| 0.8063        | 0.5223 | 80   | 0.8411          |
| 0.8782        | 0.5485 | 84   | 0.8395          |
| 0.7944        | 0.5746 | 88   | 0.8395          |
| 0.8728        | 0.6007 | 92   | 0.8370          |
| 0.7882        | 0.6268 | 96   | 0.8363          |
| 0.8999        | 0.6529 | 100  | 0.8354          |
| 0.7857        | 0.6790 | 104  | 0.8341          |
| 0.8258        | 0.7052 | 108  | 0.8331          |
| 0.7877        | 0.7313 | 112  | 0.8317          |
| 0.7686        | 0.7574 | 116  | 0.8305          |
| 0.7422        | 0.7835 | 120  | 0.8299          |
| 0.8229        | 0.8096 | 124  | 0.8292          |
| 0.7577        | 0.8357 | 128  | 0.8285          |
| 0.8811        | 0.8619 | 132  | 0.8278          |
| 0.8243        | 0.8880 | 136  | 0.8277          |
| 0.8243        | 0.9141 | 140  | 0.8275          |
| 0.8096        | 0.9402 | 144  | 0.8275          |
| 0.8476        | 0.9663 | 148  | 0.8274          |
| 0.8154        | 0.9925 | 152  | 0.8272          |


### Framework versions

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