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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_ortho_r16
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_ortho_r16
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: 1.9385
## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 32
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 2.0486 | 0.0206 | 8 | 1.9976 |
| 1.9839 | 0.0412 | 16 | 1.9348 |
| 2.0083 | 0.0618 | 24 | 1.9231 |
| 1.923 | 0.0824 | 32 | 1.9185 |
| 1.9734 | 0.1031 | 40 | 1.9200 |
| 1.9761 | 0.1237 | 48 | 1.9230 |
| 1.9869 | 0.1443 | 56 | 1.9226 |
| 1.9196 | 0.1649 | 64 | 1.9238 |
| 1.9871 | 0.1855 | 72 | 1.9276 |
| 2.0064 | 0.2061 | 80 | 1.9251 |
| 1.9864 | 0.2267 | 88 | 1.9282 |
| 1.9204 | 0.2473 | 96 | 1.9319 |
| 2.0003 | 0.2680 | 104 | 1.9295 |
| 1.8821 | 0.2886 | 112 | 1.9357 |
| 1.9353 | 0.3092 | 120 | 1.9354 |
| 1.9737 | 0.3298 | 128 | 1.9392 |
| 1.9608 | 0.3504 | 136 | 1.9337 |
| 1.928 | 0.3710 | 144 | 1.9365 |
| 2.0019 | 0.3916 | 152 | 1.9326 |
| 2.0525 | 0.4122 | 160 | 1.9403 |
| 2.053 | 0.4329 | 168 | 1.9402 |
| 1.9342 | 0.4535 | 176 | 1.9374 |
| 1.9931 | 0.4741 | 184 | 1.9400 |
| 2.0008 | 0.4947 | 192 | 1.9413 |
| 1.9426 | 0.5153 | 200 | 1.9406 |
| 1.9732 | 0.5359 | 208 | 1.9409 |
| 2.0263 | 0.5565 | 216 | 1.9431 |
| 1.9589 | 0.5771 | 224 | 1.9444 |
| 1.9824 | 0.5977 | 232 | 1.9460 |
| 1.9252 | 0.6184 | 240 | 1.9399 |
| 1.9563 | 0.6390 | 248 | 1.9400 |
| 2.0096 | 0.6596 | 256 | 1.9414 |
| 1.9355 | 0.6802 | 264 | 1.9420 |
| 2.003 | 0.7008 | 272 | 1.9415 |
| 1.877 | 0.7214 | 280 | 1.9396 |
| 2.0395 | 0.7420 | 288 | 1.9378 |
| 1.9447 | 0.7626 | 296 | 1.9382 |
| 1.965 | 0.7833 | 304 | 1.9391 |
| 1.9656 | 0.8039 | 312 | 1.9353 |
| 1.9928 | 0.8245 | 320 | 1.9398 |
| 2.0004 | 0.8451 | 328 | 1.9392 |
| 1.9883 | 0.8657 | 336 | 1.9389 |
| 1.9764 | 0.8863 | 344 | 1.9395 |
| 1.9474 | 0.9069 | 352 | 1.9390 |
| 2.0375 | 0.9275 | 360 | 1.9382 |
| 1.9424 | 0.9481 | 368 | 1.9386 |
| 2.0088 | 0.9688 | 376 | 1.9385 |
| 1.9043 | 0.9894 | 384 | 1.9385 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |