|
--- |
|
license: mit |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: deberta-classifier-feedback-1024-pseudo |
|
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. --> |
|
|
|
# deberta-classifier-feedback-1024-pseudo |
|
|
|
This model is a fine-tuned version of [TTian/deberta-classifier-feedback-1024](https://huggingface.co/TTian/deberta-classifier-feedback-1024) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.1018 |
|
|
|
## 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: 2e-05 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 16 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 3 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 0.5566 | 0.01 | 10 | 0.8514 | |
|
| 0.3244 | 0.03 | 20 | 0.8647 | |
|
| 0.2631 | 0.04 | 30 | 0.6700 | |
|
| 0.2237 | 0.06 | 40 | 0.8904 | |
|
| 0.2103 | 0.07 | 50 | 0.7951 | |
|
| 0.2576 | 0.08 | 60 | 0.8669 | |
|
| 0.2519 | 0.1 | 70 | 0.9586 | |
|
| 0.2419 | 0.11 | 80 | 0.7507 | |
|
| 0.2088 | 0.13 | 90 | 1.1316 | |
|
| 0.218 | 0.14 | 100 | 0.7750 | |
|
| 0.1886 | 0.15 | 110 | 0.9505 | |
|
| 0.1979 | 0.17 | 120 | 0.9668 | |
|
| 0.2069 | 0.18 | 130 | 0.9559 | |
|
| 0.2633 | 0.2 | 140 | 1.1578 | |
|
| 0.2176 | 0.21 | 150 | 0.9224 | |
|
| 0.2026 | 0.22 | 160 | 0.9700 | |
|
| 0.2231 | 0.24 | 170 | 1.0094 | |
|
| 0.2396 | 0.25 | 180 | 1.1268 | |
|
| 0.2172 | 0.27 | 190 | 0.9728 | |
|
| 0.2105 | 0.28 | 200 | 0.9813 | |
|
| 0.2816 | 0.29 | 210 | 0.8179 | |
|
| 0.1927 | 0.31 | 220 | 1.0210 | |
|
| 0.1686 | 0.32 | 230 | 1.0608 | |
|
| 0.1662 | 0.34 | 240 | 0.9698 | |
|
| 0.1969 | 0.35 | 250 | 0.9445 | |
|
| 0.2037 | 0.36 | 260 | 1.0223 | |
|
| 0.1684 | 0.38 | 270 | 0.9921 | |
|
| 0.1934 | 0.39 | 280 | 0.9738 | |
|
| 0.1927 | 0.41 | 290 | 0.9370 | |
|
| 0.1978 | 0.42 | 300 | 1.0144 | |
|
| 0.1591 | 0.43 | 310 | 0.9222 | |
|
| 0.1748 | 0.45 | 320 | 0.9433 | |
|
| 0.2245 | 0.46 | 330 | 0.9773 | |
|
| 0.2297 | 0.48 | 340 | 0.9884 | |
|
| 0.1746 | 0.49 | 350 | 1.0024 | |
|
| 0.152 | 0.5 | 360 | 0.9463 | |
|
| 0.1514 | 0.52 | 370 | 1.0633 | |
|
| 0.1898 | 0.53 | 380 | 1.1181 | |
|
| 0.1438 | 0.55 | 390 | 1.0994 | |
|
| 0.1426 | 0.56 | 400 | 1.0228 | |
|
| 0.1545 | 0.58 | 410 | 1.1413 | |
|
| 0.146 | 0.59 | 420 | 1.0416 | |
|
| 0.1295 | 0.6 | 430 | 1.0037 | |
|
| 0.1538 | 0.62 | 440 | 1.0532 | |
|
| 0.1584 | 0.63 | 450 | 1.1754 | |
|
| 0.1607 | 0.65 | 460 | 1.0540 | |
|
| 0.1518 | 0.66 | 470 | 1.0318 | |
|
| 0.1447 | 0.67 | 480 | 1.0777 | |
|
| 0.1432 | 0.69 | 490 | 1.0318 | |
|
| 0.1491 | 0.7 | 500 | 1.0717 | |
|
| 0.1134 | 0.72 | 510 | 1.0512 | |
|
| 0.1106 | 0.73 | 520 | 1.1904 | |
|
| 0.1521 | 0.74 | 530 | 1.0705 | |
|
| 0.1485 | 0.76 | 540 | 1.0390 | |
|
| 0.1431 | 0.77 | 550 | 1.1089 | |
|
| 0.1537 | 0.79 | 560 | 1.0316 | |
|
| 0.1472 | 0.8 | 570 | 1.1694 | |
|
| 0.129 | 0.81 | 580 | 1.1325 | |
|
| 0.1286 | 0.83 | 590 | 1.0471 | |
|
| 0.1338 | 0.84 | 600 | 1.1001 | |
|
| 0.1285 | 0.86 | 610 | 1.0770 | |
|
| 0.1379 | 0.87 | 620 | 1.1107 | |
|
| 0.1299 | 0.88 | 630 | 1.0579 | |
|
| 0.1151 | 0.9 | 640 | 1.0898 | |
|
| 0.1119 | 0.91 | 650 | 1.1335 | |
|
| 0.1297 | 0.93 | 660 | 1.1061 | |
|
| 0.1218 | 0.94 | 670 | 1.1080 | |
|
| 0.1038 | 0.95 | 680 | 1.0922 | |
|
| 0.1286 | 0.97 | 690 | 1.1035 | |
|
| 0.1263 | 0.98 | 700 | 1.1118 | |
|
| 0.1182 | 1.0 | 710 | 1.1018 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.24.0 |
|
- Pytorch 1.12.1+cu113 |
|
- Datasets 2.7.1 |
|
- Tokenizers 0.13.2 |
|
|