metadata
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_beit_large_adamax_001_fold3
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.7674418604651163
hushem_40x_beit_large_adamax_001_fold3
This model is a fine-tuned version of microsoft/beit-large-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 3.1862
- Accuracy: 0.7674
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: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3341 | 1.0 | 217 | 1.0412 | 0.6512 |
| 0.1567 | 2.0 | 434 | 0.8679 | 0.7907 |
| 0.1261 | 3.0 | 651 | 0.9519 | 0.7907 |
| 0.0451 | 4.0 | 868 | 1.0258 | 0.7674 |
| 0.0494 | 5.0 | 1085 | 1.2986 | 0.8140 |
| 0.0356 | 6.0 | 1302 | 1.5169 | 0.7442 |
| 0.0142 | 7.0 | 1519 | 1.4785 | 0.7907 |
| 0.048 | 8.0 | 1736 | 1.4460 | 0.8140 |
| 0.0363 | 9.0 | 1953 | 1.0943 | 0.7674 |
| 0.0409 | 10.0 | 2170 | 1.6345 | 0.7907 |
| 0.0021 | 11.0 | 2387 | 1.2558 | 0.8140 |
| 0.0072 | 12.0 | 2604 | 1.1994 | 0.8372 |
| 0.0193 | 13.0 | 2821 | 1.2732 | 0.8372 |
| 0.0006 | 14.0 | 3038 | 1.5708 | 0.7674 |
| 0.0013 | 15.0 | 3255 | 1.1380 | 0.8837 |
| 0.0001 | 16.0 | 3472 | 1.3578 | 0.8837 |
| 0.0 | 17.0 | 3689 | 1.3940 | 0.8837 |
| 0.0 | 18.0 | 3906 | 1.4630 | 0.8605 |
| 0.0 | 19.0 | 4123 | 1.4804 | 0.8140 |
| 0.0 | 20.0 | 4340 | 1.5039 | 0.8372 |
| 0.0 | 21.0 | 4557 | 1.5153 | 0.8605 |
| 0.0 | 22.0 | 4774 | 1.6110 | 0.8372 |
| 0.0 | 23.0 | 4991 | 1.6351 | 0.8372 |
| 0.0 | 24.0 | 5208 | 1.6586 | 0.8372 |
| 0.0 | 25.0 | 5425 | 1.6837 | 0.8605 |
| 0.0 | 26.0 | 5642 | 2.1644 | 0.8140 |
| 0.0 | 27.0 | 5859 | 1.8231 | 0.8372 |
| 0.0 | 28.0 | 6076 | 1.8592 | 0.8837 |
| 0.0 | 29.0 | 6293 | 2.3766 | 0.7907 |
| 0.0004 | 30.0 | 6510 | 2.2802 | 0.7674 |
| 0.0 | 31.0 | 6727 | 2.0919 | 0.7907 |
| 0.0 | 32.0 | 6944 | 2.0989 | 0.7907 |
| 0.0 | 33.0 | 7161 | 2.1214 | 0.7907 |
| 0.0 | 34.0 | 7378 | 2.1583 | 0.7907 |
| 0.0 | 35.0 | 7595 | 2.1876 | 0.7907 |
| 0.0 | 36.0 | 7812 | 2.1795 | 0.7907 |
| 0.0007 | 37.0 | 8029 | 3.1536 | 0.7674 |
| 0.0 | 38.0 | 8246 | 3.0845 | 0.7674 |
| 0.0 | 39.0 | 8463 | 2.9748 | 0.7907 |
| 0.0 | 40.0 | 8680 | 2.9984 | 0.7907 |
| 0.0 | 41.0 | 8897 | 3.0029 | 0.7907 |
| 0.0 | 42.0 | 9114 | 3.0143 | 0.7907 |
| 0.0 | 43.0 | 9331 | 3.0354 | 0.7907 |
| 0.0 | 44.0 | 9548 | 3.0480 | 0.7907 |
| 0.0 | 45.0 | 9765 | 3.0564 | 0.7907 |
| 0.0 | 46.0 | 9982 | 3.1685 | 0.7674 |
| 0.0 | 47.0 | 10199 | 3.1763 | 0.7674 |
| 0.0 | 48.0 | 10416 | 3.1810 | 0.7674 |
| 0.0 | 49.0 | 10633 | 3.1846 | 0.7674 |
| 0.0 | 50.0 | 10850 | 3.1862 | 0.7674 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2