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---
base_model: unsloth/Qwen2-7B
library_name: peft
license: apache-2.0
tags:
- unsloth
- generated_from_trainer
model-index:
- name: Qwen2-7B_pct_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_pct_reverse
This model is a fine-tuned version of [unsloth/Qwen2-7B](https://huggingface.co/unsloth/Qwen2-7B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0219
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 2.1146 | 0.0206 | 8 | 2.0126 |
| 2.1241 | 0.0412 | 16 | 2.0399 |
| 2.1297 | 0.0618 | 24 | 2.0522 |
| 2.0751 | 0.0824 | 32 | 2.0553 |
| 2.1182 | 0.1031 | 40 | 2.0606 |
| 2.1169 | 0.1237 | 48 | 2.0666 |
| 2.1253 | 0.1443 | 56 | 2.0730 |
| 2.1136 | 0.1649 | 64 | 2.0714 |
| 2.127 | 0.1855 | 72 | 2.0839 |
| 2.1835 | 0.2061 | 80 | 2.0803 |
| 2.1556 | 0.2267 | 88 | 2.0903 |
| 2.1396 | 0.2473 | 96 | 2.0887 |
| 2.1656 | 0.2680 | 104 | 2.0928 |
| 2.0821 | 0.2886 | 112 | 2.0880 |
| 2.1287 | 0.3092 | 120 | 2.0923 |
| 2.1298 | 0.3298 | 128 | 2.0969 |
| 2.1317 | 0.3504 | 136 | 2.0961 |
| 2.1325 | 0.3710 | 144 | 2.0906 |
| 2.1398 | 0.3916 | 152 | 2.0906 |
| 2.1569 | 0.4122 | 160 | 2.0886 |
| 2.195 | 0.4329 | 168 | 2.0862 |
| 2.1038 | 0.4535 | 176 | 2.0899 |
| 2.1159 | 0.4741 | 184 | 2.0845 |
| 2.1605 | 0.4947 | 192 | 2.0805 |
| 2.0894 | 0.5153 | 200 | 2.0765 |
| 2.1368 | 0.5359 | 208 | 2.0748 |
| 2.1626 | 0.5565 | 216 | 2.0715 |
| 2.0765 | 0.5771 | 224 | 2.0630 |
| 2.0879 | 0.5977 | 232 | 2.0677 |
| 2.0851 | 0.6184 | 240 | 2.0554 |
| 2.0731 | 0.6390 | 248 | 2.0549 |
| 2.113 | 0.6596 | 256 | 2.0517 |
| 2.0796 | 0.6802 | 264 | 2.0484 |
| 2.1406 | 0.7008 | 272 | 2.0457 |
| 2.0454 | 0.7214 | 280 | 2.0421 |
| 2.1278 | 0.7420 | 288 | 2.0378 |
| 2.0616 | 0.7626 | 296 | 2.0353 |
| 2.0697 | 0.7833 | 304 | 2.0340 |
| 2.0557 | 0.8039 | 312 | 2.0300 |
| 2.0954 | 0.8245 | 320 | 2.0304 |
| 2.094 | 0.8451 | 328 | 2.0297 |
| 2.0539 | 0.8657 | 336 | 2.0266 |
| 2.0866 | 0.8863 | 344 | 2.0250 |
| 2.061 | 0.9069 | 352 | 2.0227 |
| 2.126 | 0.9275 | 360 | 2.0220 |
| 2.0616 | 0.9481 | 368 | 2.0222 |
| 2.106 | 0.9688 | 376 | 2.0219 |
| 2.0596 | 0.9894 | 384 | 2.0219 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |