BEiT-RHS-DA
This model is a fine-tuned version of microsoft/beit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.7194
- Accuracy: 0.6355
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 40
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.2357 | 0.98 | 22 | 0.7114 | 0.5888 |
| 0.6596 | 2.0 | 45 | 0.7059 | 0.5981 |
| 0.206 | 2.98 | 67 | 1.1449 | 0.5981 |
| 0.1664 | 4.0 | 90 | 2.2062 | 0.3925 |
| 0.1011 | 4.98 | 112 | 2.0409 | 0.4673 |
| 0.0653 | 6.0 | 135 | 1.3038 | 0.6262 |
| 0.2843 | 6.98 | 157 | 1.7210 | 0.5981 |
| 0.059 | 8.0 | 180 | 2.8706 | 0.4673 |
| 0.1318 | 8.98 | 202 | 2.4519 | 0.5888 |
| 0.0501 | 10.0 | 225 | 2.2037 | 0.5888 |
| 0.054 | 10.98 | 247 | 2.6467 | 0.5888 |
| 0.0263 | 12.0 | 270 | 2.4033 | 0.5981 |
| 0.0553 | 12.98 | 292 | 1.6589 | 0.5888 |
| 0.0898 | 14.0 | 315 | 1.7657 | 0.5981 |
| 0.0324 | 14.98 | 337 | 2.8266 | 0.5888 |
| 0.0322 | 16.0 | 360 | 1.7194 | 0.6355 |
| 0.03 | 16.98 | 382 | 2.0352 | 0.6168 |
| 0.0392 | 18.0 | 405 | 2.4130 | 0.6168 |
| 0.0428 | 18.98 | 427 | 2.0628 | 0.6075 |
| 0.0127 | 20.0 | 450 | 2.7431 | 0.5888 |
| 0.0187 | 20.98 | 472 | 2.7009 | 0.5981 |
| 0.0469 | 22.0 | 495 | 2.5783 | 0.5981 |
| 0.0095 | 22.98 | 517 | 2.3040 | 0.5981 |
| 0.0025 | 24.0 | 540 | 2.5218 | 0.6168 |
| 0.0281 | 24.98 | 562 | 3.2310 | 0.5981 |
| 0.0004 | 26.0 | 585 | 3.2731 | 0.5981 |
| 0.0109 | 26.98 | 607 | 2.4809 | 0.6262 |
| 0.0191 | 28.0 | 630 | 2.7825 | 0.5888 |
| 0.0005 | 28.98 | 652 | 3.5280 | 0.5888 |
| 0.0093 | 30.0 | 675 | 2.8290 | 0.6075 |
| 0.0224 | 30.98 | 697 | 2.9546 | 0.5794 |
| 0.0011 | 32.0 | 720 | 3.0148 | 0.6075 |
| 0.003 | 32.98 | 742 | 3.2916 | 0.5981 |
| 0.0003 | 34.0 | 765 | 3.2930 | 0.5981 |
| 0.0003 | 34.98 | 787 | 3.6287 | 0.5888 |
| 0.0002 | 36.0 | 810 | 3.6918 | 0.5888 |
| 0.0004 | 36.98 | 832 | 3.6597 | 0.5888 |
| 0.0003 | 38.0 | 855 | 3.6599 | 0.5888 |
| 0.0002 | 38.98 | 877 | 3.6740 | 0.5888 |
| 0.0002 | 39.11 | 880 | 3.6741 | 0.5888 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0