vit-large-patch16-224-finetuned-ind-17-imbalanced-aadhaarmask
This model is a fine-tuned version of google/vit-large-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3294
- Accuracy: 0.8421
- Recall: 0.8421
- F1: 0.8405
- Precision: 0.8450
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | F1 | Precision |
|---|---|---|---|---|---|---|---|
| 0.5269 | 0.9974 | 293 | 0.5393 | 0.8029 | 0.8029 | 0.7943 | 0.7941 |
| 0.4275 | 1.9983 | 587 | 0.4630 | 0.8182 | 0.8182 | 0.8103 | 0.8255 |
| 0.4681 | 2.9991 | 881 | 0.4346 | 0.8408 | 0.8408 | 0.8358 | 0.8557 |
| 0.3721 | 4.0 | 1175 | 0.3631 | 0.8450 | 0.8450 | 0.8417 | 0.8541 |
| 0.4054 | 4.9974 | 1468 | 0.3536 | 0.8455 | 0.8455 | 0.8445 | 0.8491 |
| 0.2519 | 5.9983 | 1762 | 0.3747 | 0.8421 | 0.8421 | 0.8391 | 0.8549 |
| 0.2923 | 6.9991 | 2056 | 0.3664 | 0.8395 | 0.8395 | 0.8402 | 0.8467 |
| 0.2288 | 8.0 | 2350 | 0.3496 | 0.8382 | 0.8382 | 0.8377 | 0.8442 |
| 0.1642 | 8.9974 | 2643 | 0.3455 | 0.8463 | 0.8463 | 0.8444 | 0.8468 |
| 0.1783 | 9.9745 | 2930 | 0.3468 | 0.8476 | 0.8476 | 0.8463 | 0.8490 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.0a0+81ea7a4
- Datasets 2.19.0
- Tokenizers 0.19.1