metadata
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_beit_base_rms_001_fold2
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: 0.4444444444444444
hushem_5x_beit_base_rms_001_fold2
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: 3.7933
- Accuracy: 0.4444
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 |
|---|---|---|---|---|
| 1.4827 | 1.0 | 27 | 1.4775 | 0.2444 |
| 1.4158 | 2.0 | 54 | 1.4002 | 0.2667 |
| 1.3654 | 3.0 | 81 | 1.4674 | 0.2444 |
| 1.4175 | 4.0 | 108 | 1.4412 | 0.2444 |
| 1.394 | 5.0 | 135 | 1.3951 | 0.2667 |
| 1.2686 | 6.0 | 162 | 1.3983 | 0.2444 |
| 1.2556 | 7.0 | 189 | 1.4175 | 0.2889 |
| 1.2245 | 8.0 | 216 | 1.4754 | 0.2222 |
| 1.1427 | 9.0 | 243 | 1.5387 | 0.2 |
| 1.1659 | 10.0 | 270 | 1.3896 | 0.3333 |
| 1.2047 | 11.0 | 297 | 1.6922 | 0.2444 |
| 1.1384 | 12.0 | 324 | 1.4940 | 0.2667 |
| 1.1563 | 13.0 | 351 | 1.3730 | 0.2889 |
| 1.1141 | 14.0 | 378 | 1.4944 | 0.2222 |
| 1.0922 | 15.0 | 405 | 1.4049 | 0.2222 |
| 1.0475 | 16.0 | 432 | 1.2541 | 0.4 |
| 0.9208 | 17.0 | 459 | 1.2993 | 0.4222 |
| 0.9847 | 18.0 | 486 | 1.4111 | 0.4889 |
| 0.9327 | 19.0 | 513 | 1.3175 | 0.2889 |
| 0.8591 | 20.0 | 540 | 1.2892 | 0.3111 |
| 0.7605 | 21.0 | 567 | 1.6440 | 0.2667 |
| 0.7953 | 22.0 | 594 | 1.6915 | 0.3778 |
| 0.7644 | 23.0 | 621 | 1.6017 | 0.4667 |
| 0.7884 | 24.0 | 648 | 1.4064 | 0.2444 |
| 0.6883 | 25.0 | 675 | 1.9722 | 0.3111 |
| 0.7747 | 26.0 | 702 | 1.9209 | 0.4889 |
| 0.7012 | 27.0 | 729 | 2.2074 | 0.5333 |
| 0.6951 | 28.0 | 756 | 2.4602 | 0.3556 |
| 0.6581 | 29.0 | 783 | 2.1544 | 0.4222 |
| 0.6529 | 30.0 | 810 | 2.0677 | 0.3556 |
| 0.533 | 31.0 | 837 | 2.1507 | 0.3778 |
| 0.6648 | 32.0 | 864 | 2.1628 | 0.4222 |
| 0.6094 | 33.0 | 891 | 2.5365 | 0.3778 |
| 0.5601 | 34.0 | 918 | 2.8323 | 0.4222 |
| 0.519 | 35.0 | 945 | 2.4166 | 0.4 |
| 0.5988 | 36.0 | 972 | 2.6302 | 0.4444 |
| 0.5359 | 37.0 | 999 | 2.9183 | 0.3778 |
| 0.5451 | 38.0 | 1026 | 2.8746 | 0.5111 |
| 0.5087 | 39.0 | 1053 | 2.7419 | 0.4667 |
| 0.4563 | 40.0 | 1080 | 3.1565 | 0.4222 |
| 0.5182 | 41.0 | 1107 | 3.1768 | 0.4444 |
| 0.4348 | 42.0 | 1134 | 3.2761 | 0.4222 |
| 0.4504 | 43.0 | 1161 | 3.4108 | 0.4667 |
| 0.417 | 44.0 | 1188 | 3.5781 | 0.4444 |
| 0.4297 | 45.0 | 1215 | 3.6284 | 0.4444 |
| 0.3399 | 46.0 | 1242 | 3.7187 | 0.4444 |
| 0.3846 | 47.0 | 1269 | 3.7298 | 0.4667 |
| 0.3494 | 48.0 | 1296 | 3.7854 | 0.4444 |
| 0.3468 | 49.0 | 1323 | 3.7933 | 0.4444 |
| 0.3313 | 50.0 | 1350 | 3.7933 | 0.4444 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0