---
license: apache-2.0
library_name: peft
tags:
- unsloth
- generated_from_trainer
base_model: Qwen/Qwen2-7B
model-index:
- name: qwen2_Magiccoder_evol_10k_qlora_ortho
  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_qlora_ortho

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: 0.9025

## 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: 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_steps: 0.02
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8992        | 0.0261 | 4    | 0.9547          |
| 0.9045        | 0.0522 | 8    | 0.9234          |
| 0.9145        | 0.0783 | 12   | 0.9166          |
| 0.8688        | 0.1044 | 16   | 0.9117          |
| 0.9222        | 0.1305 | 20   | 0.9097          |
| 0.8108        | 0.1566 | 24   | 0.9090          |
| 0.8194        | 0.1827 | 28   | 0.9083          |
| 0.9616        | 0.2088 | 32   | 0.9086          |
| 0.8624        | 0.2349 | 36   | 0.9083          |
| 0.8898        | 0.2610 | 40   | 0.9088          |
| 0.9476        | 0.2871 | 44   | 0.9085          |
| 0.9156        | 0.3132 | 48   | 0.9091          |
| 0.8388        | 0.3393 | 52   | 0.9091          |
| 0.8429        | 0.3654 | 56   | 0.9087          |
| 0.8651        | 0.3915 | 60   | 0.9081          |
| 0.9228        | 0.4176 | 64   | 0.9082          |
| 0.9167        | 0.4437 | 68   | 0.9076          |
| 0.8769        | 0.4698 | 72   | 0.9068          |
| 0.9009        | 0.4959 | 76   | 0.9069          |
| 0.8611        | 0.5220 | 80   | 0.9074          |
| 0.9496        | 0.5481 | 84   | 0.9070          |
| 0.8562        | 0.5742 | 88   | 0.9067          |
| 0.943         | 0.6003 | 92   | 0.9060          |
| 0.8718        | 0.6264 | 96   | 0.9053          |
| 0.9642        | 0.6525 | 100  | 0.9046          |
| 0.8425        | 0.6786 | 104  | 0.9042          |
| 0.886         | 0.7047 | 108  | 0.9040          |
| 0.8576        | 0.7308 | 112  | 0.9043          |
| 0.823         | 0.7569 | 116  | 0.9036          |
| 0.8158        | 0.7830 | 120  | 0.9032          |
| 0.8854        | 0.8091 | 124  | 0.9031          |
| 0.8502        | 0.8352 | 128  | 0.9030          |
| 0.9493        | 0.8613 | 132  | 0.9026          |
| 0.8934        | 0.8874 | 136  | 0.9026          |
| 0.9158        | 0.9135 | 140  | 0.9026          |
| 0.8686        | 0.9396 | 144  | 0.9026          |
| 0.9321        | 0.9657 | 148  | 0.9027          |
| 0.8882        | 0.9918 | 152  | 0.9025          |


### Framework versions

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