beit-base-patch16-224-RD
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: 0.3771
- Accuracy: 0.8673
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: 0.1
- num_epochs: 40
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.4986 | 0.99 | 40 | 1.4512 | 0.4945 |
| 1.0553 | 1.99 | 80 | 0.9355 | 0.7473 |
| 0.7972 | 2.98 | 120 | 0.7250 | 0.7436 |
| 0.7156 | 4.0 | 161 | 0.5845 | 0.7582 |
| 0.6723 | 4.99 | 201 | 0.5509 | 0.8036 |
| 0.5942 | 5.99 | 241 | 0.5018 | 0.8218 |
| 0.6223 | 6.98 | 281 | 0.4993 | 0.8218 |
| 0.5731 | 8.0 | 322 | 0.4590 | 0.8291 |
| 0.5583 | 8.99 | 362 | 0.4878 | 0.8 |
| 0.5784 | 9.99 | 402 | 0.4485 | 0.8455 |
| 0.4968 | 10.98 | 442 | 0.4305 | 0.8345 |
| 0.5324 | 12.0 | 483 | 0.4737 | 0.8345 |
| 0.4629 | 12.99 | 523 | 0.4253 | 0.8436 |
| 0.4398 | 13.99 | 563 | 0.4184 | 0.8473 |
| 0.4575 | 14.98 | 603 | 0.3929 | 0.8564 |
| 0.4554 | 16.0 | 644 | 0.4282 | 0.8491 |
| 0.4646 | 16.99 | 684 | 0.4363 | 0.8236 |
| 0.4535 | 17.99 | 724 | 0.4337 | 0.8455 |
| 0.3823 | 18.98 | 764 | 0.3771 | 0.8673 |
| 0.4584 | 20.0 | 805 | 0.3966 | 0.8564 |
| 0.4103 | 20.99 | 845 | 0.4001 | 0.8491 |
| 0.3659 | 21.99 | 885 | 0.3948 | 0.8582 |
| 0.3241 | 22.98 | 925 | 0.4007 | 0.8582 |
| 0.3575 | 24.0 | 966 | 0.4328 | 0.8327 |
| 0.3411 | 24.99 | 1006 | 0.3990 | 0.8564 |
| 0.3829 | 25.99 | 1046 | 0.4011 | 0.8636 |
| 0.2855 | 26.98 | 1086 | 0.3859 | 0.8655 |
| 0.254 | 28.0 | 1127 | 0.4196 | 0.8673 |
| 0.2937 | 28.99 | 1167 | 0.4340 | 0.8618 |
| 0.258 | 29.99 | 1207 | 0.4387 | 0.8509 |
| 0.2735 | 30.98 | 1247 | 0.4097 | 0.8655 |
| 0.2674 | 32.0 | 1288 | 0.4183 | 0.8527 |
| 0.2547 | 32.99 | 1328 | 0.4217 | 0.8636 |
| 0.2109 | 33.99 | 1368 | 0.4240 | 0.8527 |
| 0.2248 | 34.98 | 1408 | 0.4250 | 0.86 |
| 0.2397 | 36.0 | 1449 | 0.4431 | 0.8582 |
| 0.1823 | 36.99 | 1489 | 0.4442 | 0.8582 |
| 0.1834 | 37.99 | 1529 | 0.4362 | 0.8618 |
| 0.1864 | 38.98 | 1569 | 0.4338 | 0.8545 |
| 0.1779 | 39.75 | 1600 | 0.4332 | 0.8582 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0