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---
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_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-bnb-4bit](https://huggingface.co./unsloth/qwen2-7b-bnb-4bit) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0907
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.9111 | 0.0261 | 4 | 0.9716 |
| 1.0695 | 0.0522 | 8 | 1.1827 |
| 1.1409 | 0.0783 | 12 | 1.1378 |
| 1.1017 | 0.1044 | 16 | 1.1270 |
| 1.1579 | 0.1305 | 20 | 1.1441 |
| 1.0234 | 0.1566 | 24 | 1.1212 |
| 1.0225 | 0.1827 | 28 | 1.1567 |
| 1.1587 | 0.2088 | 32 | 1.1425 |
| 1.0519 | 0.2349 | 36 | 1.1214 |
| 1.1006 | 0.2610 | 40 | 1.1195 |
| 1.1443 | 0.2871 | 44 | 1.1159 |
| 1.1088 | 0.3132 | 48 | 1.1123 |
| 1.0303 | 0.3393 | 52 | 1.1125 |
| 1.0499 | 0.3654 | 56 | 1.1232 |
| 1.082 | 0.3915 | 60 | 1.1239 |
| 1.1319 | 0.4176 | 64 | 1.1299 |
| 1.1228 | 0.4437 | 68 | 1.1170 |
| 1.0796 | 0.4698 | 72 | 1.1129 |
| 1.0974 | 0.4959 | 76 | 1.1162 |
| 1.0566 | 0.5220 | 80 | 1.1066 |
| 1.1243 | 0.5481 | 84 | 1.1036 |
| 1.0449 | 0.5742 | 88 | 1.1075 |
| 1.1215 | 0.6003 | 92 | 1.1022 |
| 1.0506 | 0.6264 | 96 | 1.0941 |
| 1.1367 | 0.6525 | 100 | 1.0924 |
| 1.03 | 0.6786 | 104 | 1.1014 |
| 1.0844 | 0.7047 | 108 | 1.1160 |
| 1.0575 | 0.7308 | 112 | 1.1058 |
| 1.0169 | 0.7569 | 116 | 1.1061 |
| 1.002 | 0.7830 | 120 | 1.1091 |
| 1.0741 | 0.8091 | 124 | 1.1094 |
| 1.0651 | 0.8352 | 128 | 1.1032 |
| 1.1222 | 0.8613 | 132 | 1.0976 |
| 1.0595 | 0.8874 | 136 | 1.0952 |
| 1.0879 | 0.9135 | 140 | 1.0931 |
| 1.0433 | 0.9396 | 144 | 1.0917 |
| 1.1012 | 0.9657 | 148 | 1.0908 |
| 1.0587 | 0.9918 | 152 | 1.0907 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |