|
--- |
|
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 |
