---
base_model: unsloth/qwen2-7b-bnb-4bit
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-bnb-4bit](https://huggingface.co./unsloth/qwen2-7b-bnb-4bit) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8796

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.9592        | 0.0261 | 4    | 1.0014          |
| 0.9246        | 0.0522 | 8    | 0.9342          |
| 0.9101        | 0.0783 | 12   | 0.9148          |
| 0.8605        | 0.1044 | 16   | 0.9008          |
| 0.9093        | 0.1305 | 20   | 0.8958          |
| 0.7967        | 0.1566 | 24   | 0.8949          |
| 0.8075        | 0.1827 | 28   | 0.8941          |
| 0.9522        | 0.2088 | 32   | 0.8917          |
| 0.8503        | 0.2349 | 36   | 0.8890          |
| 0.8704        | 0.2610 | 40   | 0.8864          |
| 0.9286        | 0.2871 | 44   | 0.8852          |
| 0.894         | 0.3132 | 48   | 0.8839          |
| 0.8171        | 0.3393 | 52   | 0.8835          |
| 0.8224        | 0.3654 | 56   | 0.8828          |
| 0.8392        | 0.3915 | 60   | 0.8822          |
| 0.897         | 0.4176 | 64   | 0.8817          |
| 0.8942        | 0.4437 | 68   | 0.8813          |
| 0.8501        | 0.4698 | 72   | 0.8809          |
| 0.8768        | 0.4959 | 76   | 0.8807          |
| 0.8337        | 0.5220 | 80   | 0.8806          |
| 0.9285        | 0.5481 | 84   | 0.8801          |
| 0.8301        | 0.5742 | 88   | 0.8803          |
| 0.9212        | 0.6003 | 92   | 0.8805          |
| 0.8485        | 0.6264 | 96   | 0.8804          |
| 0.9419        | 0.6525 | 100  | 0.8801          |
| 0.8191        | 0.6786 | 104  | 0.8799          |
| 0.8668        | 0.7047 | 108  | 0.8799          |
| 0.8335        | 0.7308 | 112  | 0.8798          |
| 0.8003        | 0.7569 | 116  | 0.8797          |
| 0.794         | 0.7830 | 120  | 0.8796          |
| 0.863         | 0.8091 | 124  | 0.8797          |
| 0.8262        | 0.8352 | 128  | 0.8795          |
| 0.9269        | 0.8613 | 132  | 0.8796          |
| 0.876         | 0.8874 | 136  | 0.8795          |
| 0.8955        | 0.9135 | 140  | 0.8794          |
| 0.8481        | 0.9396 | 144  | 0.8796          |
| 0.9111        | 0.9657 | 148  | 0.8795          |
| 0.8653        | 0.9918 | 152  | 0.8796          |


### Framework versions

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