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deberta-classifier-feedback-1024
This model is a fine-tuned version of TTian/deberta-mlm-feedback-1024 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6246
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 |
|---|---|---|---|
| 1.038 | 0.04 | 10 | 0.8470 |
| 0.8858 | 0.08 | 20 | 0.7317 |
| 0.8166 | 0.13 | 30 | 0.8127 |
| 0.7791 | 0.17 | 40 | 0.8111 |
| 0.7977 | 0.21 | 50 | 0.7540 |
| 0.7815 | 0.25 | 60 | 0.7204 |
| 0.7467 | 0.3 | 70 | 0.7446 |
| 0.7525 | 0.34 | 80 | 0.7522 |
| 0.716 | 0.38 | 90 | 0.7542 |
| 0.7617 | 0.42 | 100 | 0.7095 |
| 0.7618 | 0.47 | 110 | 0.7147 |
| 0.7297 | 0.51 | 120 | 0.8648 |
| 0.7797 | 0.55 | 130 | 0.7150 |
| 0.7466 | 0.59 | 140 | 0.7360 |
| 0.745 | 0.64 | 150 | 0.6842 |
| 0.718 | 0.68 | 160 | 0.7408 |
| 0.7455 | 0.72 | 170 | 0.7029 |
| 0.7476 | 0.76 | 180 | 0.7106 |
| 0.695 | 0.81 | 190 | 0.6781 |
| 0.6603 | 0.85 | 200 | 0.7713 |
| 0.7763 | 0.89 | 210 | 0.7619 |
| 0.6858 | 0.93 | 220 | 0.7252 |
| 0.6567 | 0.97 | 230 | 0.7017 |
| 0.6529 | 1.02 | 240 | 0.7030 |
| 0.6752 | 1.06 | 250 | 0.6717 |
| 0.7078 | 1.1 | 260 | 0.6868 |
| 0.6428 | 1.14 | 270 | 0.6694 |
| 0.6173 | 1.19 | 280 | 0.7137 |
| 0.6753 | 1.23 | 290 | 0.7363 |
| 0.6326 | 1.27 | 300 | 0.6808 |
| 0.6241 | 1.31 | 310 | 0.6855 |
| 0.6717 | 1.36 | 320 | 0.6627 |
| 0.633 | 1.4 | 330 | 0.7079 |
| 0.6541 | 1.44 | 340 | 0.6475 |
| 0.5998 | 1.48 | 350 | 0.7008 |
| 0.7088 | 1.53 | 360 | 0.6558 |
| 0.6209 | 1.57 | 370 | 0.6536 |
| 0.6159 | 1.61 | 380 | 0.6805 |
| 0.6297 | 1.65 | 390 | 0.6617 |
| 0.6506 | 1.69 | 400 | 0.6459 |
| 0.6397 | 1.74 | 410 | 0.6450 |
| 0.6181 | 1.78 | 420 | 0.7158 |
| 0.6609 | 1.82 | 430 | 0.6336 |
| 0.6066 | 1.86 | 440 | 0.6232 |
| 0.6418 | 1.91 | 450 | 0.6272 |
| 0.6499 | 1.95 | 460 | 0.6268 |
| 0.6021 | 1.99 | 470 | 0.6431 |
| 0.5899 | 2.03 | 480 | 0.6395 |
| 0.5524 | 2.08 | 490 | 0.6278 |
| 0.5182 | 2.12 | 500 | 0.6690 |
| 0.5768 | 2.16 | 510 | 0.6400 |
| 0.5326 | 2.2 | 520 | 0.6386 |
| 0.5641 | 2.25 | 530 | 0.6759 |
| 0.5794 | 2.29 | 540 | 0.6483 |
| 0.5341 | 2.33 | 550 | 0.6273 |
| 0.5604 | 2.37 | 560 | 0.6393 |
| 0.529 | 2.42 | 570 | 0.6389 |
| 0.5433 | 2.46 | 580 | 0.6272 |
| 0.5574 | 2.5 | 590 | 0.6387 |
| 0.5279 | 2.54 | 600 | 0.6613 |
| 0.5066 | 2.58 | 610 | 0.6376 |
| 0.5235 | 2.63 | 620 | 0.6449 |
| 0.516 | 2.67 | 630 | 0.6285 |
| 0.5888 | 2.71 | 640 | 0.6391 |
| 0.5326 | 2.75 | 650 | 0.6226 |
| 0.5486 | 2.8 | 660 | 0.6373 |
| 0.5176 | 2.84 | 670 | 0.6272 |
| 0.5038 | 2.88 | 680 | 0.6235 |
| 0.5335 | 2.92 | 690 | 0.6266 |
| 0.557 | 2.97 | 700 | 0.6246 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.0
- Tokenizers 0.13.2
