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_fold5
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: 0.8048780487804879
hushem_40x_beit_large_adamax_001_fold5
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: 1.1906
- Accuracy: 0.8049
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 |
|---|---|---|---|---|
| 0.3728 | 1.0 | 220 | 0.2484 | 0.9024 |
| 0.2424 | 2.0 | 440 | 1.0593 | 0.7805 |
| 0.1221 | 3.0 | 660 | 0.9944 | 0.7317 |
| 0.0746 | 4.0 | 880 | 1.4179 | 0.7073 |
| 0.0501 | 5.0 | 1100 | 0.6557 | 0.8049 |
| 0.0914 | 6.0 | 1320 | 1.5051 | 0.7073 |
| 0.0408 | 7.0 | 1540 | 0.1238 | 0.9512 |
| 0.0281 | 8.0 | 1760 | 0.6572 | 0.8537 |
| 0.0024 | 9.0 | 1980 | 0.9478 | 0.8049 |
| 0.0097 | 10.0 | 2200 | 0.6899 | 0.8537 |
| 0.0507 | 11.0 | 2420 | 1.0591 | 0.8049 |
| 0.0001 | 12.0 | 2640 | 0.9070 | 0.8780 |
| 0.0056 | 13.0 | 2860 | 1.1233 | 0.7805 |
| 0.0168 | 14.0 | 3080 | 1.3279 | 0.8049 |
| 0.0205 | 15.0 | 3300 | 1.4696 | 0.8049 |
| 0.0004 | 16.0 | 3520 | 1.8691 | 0.7561 |
| 0.0001 | 17.0 | 3740 | 1.4193 | 0.8293 |
| 0.0029 | 18.0 | 3960 | 1.9471 | 0.8049 |
| 0.0 | 19.0 | 4180 | 1.9190 | 0.7317 |
| 0.0 | 20.0 | 4400 | 2.0689 | 0.7317 |
| 0.0021 | 21.0 | 4620 | 0.3369 | 0.9024 |
| 0.0001 | 22.0 | 4840 | 0.9862 | 0.8537 |
| 0.0001 | 23.0 | 5060 | 0.9863 | 0.8780 |
| 0.0118 | 24.0 | 5280 | 1.0405 | 0.8049 |
| 0.0016 | 25.0 | 5500 | 1.4400 | 0.7805 |
| 0.0379 | 26.0 | 5720 | 1.0773 | 0.8537 |
| 0.0 | 27.0 | 5940 | 0.9902 | 0.8537 |
| 0.0 | 28.0 | 6160 | 0.9125 | 0.8293 |
| 0.0 | 29.0 | 6380 | 0.8492 | 0.8293 |
| 0.0 | 30.0 | 6600 | 1.3170 | 0.8293 |
| 0.0 | 31.0 | 6820 | 1.3145 | 0.7805 |
| 0.0 | 32.0 | 7040 | 0.7274 | 0.8780 |
| 0.0 | 33.0 | 7260 | 0.7992 | 0.8780 |
| 0.0 | 34.0 | 7480 | 0.7001 | 0.9024 |
| 0.0 | 35.0 | 7700 | 0.7059 | 0.9024 |
| 0.0 | 36.0 | 7920 | 0.7509 | 0.9024 |
| 0.0 | 37.0 | 8140 | 0.7646 | 0.9024 |
| 0.0 | 38.0 | 8360 | 1.2149 | 0.8293 |
| 0.0 | 39.0 | 8580 | 1.2146 | 0.8293 |
| 0.0 | 40.0 | 8800 | 1.2180 | 0.8293 |
| 0.0 | 41.0 | 9020 | 1.1864 | 0.8049 |
| 0.0 | 42.0 | 9240 | 1.1736 | 0.8049 |
| 0.0 | 43.0 | 9460 | 1.1601 | 0.8049 |
| 0.0 | 44.0 | 9680 | 1.1683 | 0.8049 |
| 0.0 | 45.0 | 9900 | 1.1682 | 0.8049 |
| 0.0 | 46.0 | 10120 | 1.1690 | 0.8049 |
| 0.0 | 47.0 | 10340 | 1.1691 | 0.8049 |
| 0.0 | 48.0 | 10560 | 1.1738 | 0.8049 |
| 0.0 | 49.0 | 10780 | 1.1753 | 0.8049 |
| 0.0 | 50.0 | 11000 | 1.1906 | 0.8049 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2