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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_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_reverse_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: 1.9143
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 2.0341 | 0.0206 | 8 | 1.9528 |
| 2.0078 | 0.0412 | 16 | 1.9550 |
| 2.0269 | 0.0618 | 24 | 1.9357 |
| 1.9472 | 0.0824 | 32 | 1.9405 |
| 1.993 | 0.1031 | 40 | 1.9381 |
| 1.9936 | 0.1237 | 48 | 1.9402 |
| 2.0043 | 0.1443 | 56 | 1.9410 |
| 1.9356 | 0.1649 | 64 | 1.9369 |
| 1.9953 | 0.1855 | 72 | 1.9396 |
| 2.0184 | 0.2061 | 80 | 1.9405 |
| 1.995 | 0.2267 | 88 | 1.9410 |
| 1.9307 | 0.2473 | 96 | 1.9407 |
| 2.0037 | 0.2680 | 104 | 1.9414 |
| 1.889 | 0.2886 | 112 | 1.9397 |
| 1.9455 | 0.3092 | 120 | 1.9401 |
| 1.9789 | 0.3298 | 128 | 1.9438 |
| 1.9642 | 0.3504 | 136 | 1.9408 |
| 1.9387 | 0.3710 | 144 | 1.9405 |
| 2.0036 | 0.3916 | 152 | 1.9394 |
| 2.0407 | 0.4122 | 160 | 1.9393 |
| 2.0519 | 0.4329 | 168 | 1.9385 |
| 1.9361 | 0.4535 | 176 | 1.9396 |
| 1.9812 | 0.4741 | 184 | 1.9404 |
| 1.9947 | 0.4947 | 192 | 1.9382 |
| 1.9343 | 0.5153 | 200 | 1.9353 |
| 1.9707 | 0.5359 | 208 | 1.9357 |
| 2.0131 | 0.5565 | 216 | 1.9351 |
| 1.9416 | 0.5771 | 224 | 1.9310 |
| 1.9652 | 0.5977 | 232 | 1.9351 |
| 1.9156 | 0.6184 | 240 | 1.9266 |
| 1.9405 | 0.6390 | 248 | 1.9260 |
| 1.9909 | 0.6596 | 256 | 1.9250 |
| 1.9179 | 0.6802 | 264 | 1.9232 |
| 1.9877 | 0.7008 | 272 | 1.9217 |
| 1.8745 | 0.7214 | 280 | 1.9207 |
| 2.016 | 0.7420 | 288 | 1.9195 |
| 1.9238 | 0.7626 | 296 | 1.9185 |
| 1.9414 | 0.7833 | 304 | 1.9193 |
| 1.9417 | 0.8039 | 312 | 1.9172 |
| 1.9647 | 0.8245 | 320 | 1.9169 |
| 1.9704 | 0.8451 | 328 | 1.9172 |
| 1.9629 | 0.8657 | 336 | 1.9157 |
| 1.9574 | 0.8863 | 344 | 1.9150 |
| 1.9278 | 0.9069 | 352 | 1.9143 |
| 2.0079 | 0.9275 | 360 | 1.9140 |
| 1.9203 | 0.9481 | 368 | 1.9138 |
| 1.9834 | 0.9688 | 376 | 1.9139 |
| 1.8809 | 0.9894 | 384 | 1.9143 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |