metadata
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_3x_beit_base_sgd_001_fold1
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: 0.8681135225375626
smids_3x_beit_base_sgd_001_fold1
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: 0.3433
- Accuracy: 0.8681
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 |
---|---|---|---|---|
0.8537 | 1.0 | 226 | 0.8519 | 0.6194 |
0.627 | 2.0 | 452 | 0.6595 | 0.7162 |
0.5599 | 3.0 | 678 | 0.5836 | 0.7563 |
0.5294 | 4.0 | 904 | 0.5378 | 0.7830 |
0.541 | 5.0 | 1130 | 0.5094 | 0.7930 |
0.4706 | 6.0 | 1356 | 0.4828 | 0.8030 |
0.4252 | 7.0 | 1582 | 0.4633 | 0.8264 |
0.4132 | 8.0 | 1808 | 0.4456 | 0.8214 |
0.3872 | 9.0 | 2034 | 0.4395 | 0.8197 |
0.4235 | 10.0 | 2260 | 0.4220 | 0.8347 |
0.363 | 11.0 | 2486 | 0.4107 | 0.8414 |
0.3912 | 12.0 | 2712 | 0.4033 | 0.8381 |
0.304 | 13.0 | 2938 | 0.4009 | 0.8381 |
0.3002 | 14.0 | 3164 | 0.4007 | 0.8414 |
0.3207 | 15.0 | 3390 | 0.3907 | 0.8431 |
0.3295 | 16.0 | 3616 | 0.3840 | 0.8481 |
0.2579 | 17.0 | 3842 | 0.3879 | 0.8447 |
0.2728 | 18.0 | 4068 | 0.3774 | 0.8514 |
0.2754 | 19.0 | 4294 | 0.3738 | 0.8514 |
0.2647 | 20.0 | 4520 | 0.3691 | 0.8531 |
0.2981 | 21.0 | 4746 | 0.3671 | 0.8548 |
0.2768 | 22.0 | 4972 | 0.3598 | 0.8614 |
0.3183 | 23.0 | 5198 | 0.3674 | 0.8548 |
0.2945 | 24.0 | 5424 | 0.3555 | 0.8598 |
0.2478 | 25.0 | 5650 | 0.3546 | 0.8648 |
0.325 | 26.0 | 5876 | 0.3592 | 0.8564 |
0.2291 | 27.0 | 6102 | 0.3605 | 0.8548 |
0.2815 | 28.0 | 6328 | 0.3547 | 0.8564 |
0.2072 | 29.0 | 6554 | 0.3519 | 0.8614 |
0.3343 | 30.0 | 6780 | 0.3526 | 0.8631 |
0.2535 | 31.0 | 7006 | 0.3589 | 0.8614 |
0.25 | 32.0 | 7232 | 0.3529 | 0.8648 |
0.21 | 33.0 | 7458 | 0.3549 | 0.8581 |
0.2119 | 34.0 | 7684 | 0.3504 | 0.8598 |
0.2671 | 35.0 | 7910 | 0.3485 | 0.8648 |
0.2299 | 36.0 | 8136 | 0.3541 | 0.8614 |
0.2465 | 37.0 | 8362 | 0.3470 | 0.8631 |
0.2631 | 38.0 | 8588 | 0.3446 | 0.8648 |
0.239 | 39.0 | 8814 | 0.3471 | 0.8598 |
0.1883 | 40.0 | 9040 | 0.3479 | 0.8648 |
0.226 | 41.0 | 9266 | 0.3450 | 0.8681 |
0.258 | 42.0 | 9492 | 0.3451 | 0.8698 |
0.2562 | 43.0 | 9718 | 0.3456 | 0.8681 |
0.1938 | 44.0 | 9944 | 0.3435 | 0.8681 |
0.2807 | 45.0 | 10170 | 0.3449 | 0.8664 |
0.253 | 46.0 | 10396 | 0.3419 | 0.8698 |
0.2465 | 47.0 | 10622 | 0.3435 | 0.8664 |
0.2602 | 48.0 | 10848 | 0.3432 | 0.8664 |
0.2179 | 49.0 | 11074 | 0.3434 | 0.8681 |
0.2786 | 50.0 | 11300 | 0.3433 | 0.8681 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2