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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_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_pct_default
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: 2.0259
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 2.1169 | 0.0206 | 8 | 2.0201 |
| 2.1264 | 0.0412 | 16 | 2.0886 |
| 2.1468 | 0.0618 | 24 | 2.0745 |
| 2.0954 | 0.0824 | 32 | 2.0725 |
| 2.136 | 0.1031 | 40 | 2.0759 |
| 2.1289 | 0.1237 | 48 | 2.1111 |
| 2.131 | 0.1443 | 56 | 2.0744 |
| 2.1168 | 0.1649 | 64 | 2.0766 |
| 2.149 | 0.1855 | 72 | 2.1028 |
| 2.1947 | 0.2061 | 80 | 2.0999 |
| 2.1727 | 0.2267 | 88 | 2.0999 |
| 2.1438 | 0.2473 | 96 | 2.0979 |
| 2.1639 | 0.2680 | 104 | 2.0984 |
| 2.0768 | 0.2886 | 112 | 2.0967 |
| 2.1262 | 0.3092 | 120 | 2.0943 |
| 2.1261 | 0.3298 | 128 | 2.0995 |
| 2.1411 | 0.3504 | 136 | 2.1028 |
| 2.1369 | 0.3710 | 144 | 2.1030 |
| 2.1419 | 0.3916 | 152 | 2.0989 |
| 2.165 | 0.4122 | 160 | 2.0972 |
| 2.1948 | 0.4329 | 168 | 2.0925 |
| 2.1076 | 0.4535 | 176 | 2.0968 |
| 2.1183 | 0.4741 | 184 | 2.0916 |
| 2.16 | 0.4947 | 192 | 2.0885 |
| 2.0938 | 0.5153 | 200 | 2.0884 |
| 2.1387 | 0.5359 | 208 | 2.0866 |
| 2.1735 | 0.5565 | 216 | 2.0854 |
| 2.0786 | 0.5771 | 224 | 2.0755 |
| 2.0929 | 0.5977 | 232 | 2.0793 |
| 2.0871 | 0.6184 | 240 | 2.0635 |
| 2.0744 | 0.6390 | 248 | 2.0637 |
| 2.1142 | 0.6596 | 256 | 2.0616 |
| 2.0861 | 0.6802 | 264 | 2.0570 |
| 2.1428 | 0.7008 | 272 | 2.0534 |
| 2.0474 | 0.7214 | 280 | 2.0486 |
| 2.1296 | 0.7420 | 288 | 2.0439 |
| 2.062 | 0.7626 | 296 | 2.0425 |
| 2.0758 | 0.7833 | 304 | 2.0405 |
| 2.0604 | 0.8039 | 312 | 2.0370 |
| 2.0963 | 0.8245 | 320 | 2.0361 |
| 2.0926 | 0.8451 | 328 | 2.0342 |
| 2.0571 | 0.8657 | 336 | 2.0307 |
| 2.0858 | 0.8863 | 344 | 2.0297 |
| 2.066 | 0.9069 | 352 | 2.0270 |
| 2.1284 | 0.9275 | 360 | 2.0260 |
| 2.0618 | 0.9481 | 368 | 2.0257 |
| 2.1074 | 0.9688 | 376 | 2.0256 |
| 2.0625 | 0.9894 | 384 | 2.0259 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |