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_0001_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: 0.5111111111111111
hushem_5x_beit_base_rms_0001_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: 6.9592
- Accuracy: 0.5111
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: 0.0001
- 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 |
|---|---|---|---|---|
| 1.3984 | 1.0 | 27 | 1.3816 | 0.2889 |
| 1.3107 | 2.0 | 54 | 1.6609 | 0.2889 |
| 1.229 | 3.0 | 81 | 1.5449 | 0.2889 |
| 1.3814 | 4.0 | 108 | 1.6341 | 0.2889 |
| 1.2031 | 5.0 | 135 | 1.4184 | 0.2667 |
| 1.1619 | 6.0 | 162 | 1.4603 | 0.2889 |
| 1.1757 | 7.0 | 189 | 1.4200 | 0.2889 |
| 1.1575 | 8.0 | 216 | 1.3581 | 0.2889 |
| 1.0419 | 9.0 | 243 | 1.5164 | 0.4 |
| 1.0334 | 10.0 | 270 | 1.3939 | 0.4889 |
| 0.799 | 11.0 | 297 | 1.4216 | 0.5333 |
| 0.7589 | 12.0 | 324 | 1.5018 | 0.5111 |
| 0.7466 | 13.0 | 351 | 1.2714 | 0.3778 |
| 0.7077 | 14.0 | 378 | 1.2899 | 0.4 |
| 0.7022 | 15.0 | 405 | 1.4427 | 0.3333 |
| 0.6019 | 16.0 | 432 | 1.5793 | 0.4 |
| 0.6413 | 17.0 | 459 | 1.5251 | 0.3111 |
| 0.6003 | 18.0 | 486 | 2.0148 | 0.4889 |
| 0.5924 | 19.0 | 513 | 2.2670 | 0.4889 |
| 0.5357 | 20.0 | 540 | 2.0323 | 0.3556 |
| 0.5196 | 21.0 | 567 | 2.5285 | 0.4889 |
| 0.5137 | 22.0 | 594 | 3.7709 | 0.4222 |
| 0.4488 | 23.0 | 621 | 3.1001 | 0.5111 |
| 0.4667 | 24.0 | 648 | 2.9452 | 0.4 |
| 0.3277 | 25.0 | 675 | 2.8861 | 0.4667 |
| 0.3619 | 26.0 | 702 | 3.3939 | 0.5111 |
| 0.3379 | 27.0 | 729 | 3.5247 | 0.5333 |
| 0.2572 | 28.0 | 756 | 4.2104 | 0.5111 |
| 0.2257 | 29.0 | 783 | 3.4821 | 0.4889 |
| 0.2189 | 30.0 | 810 | 3.8860 | 0.4667 |
| 0.1431 | 31.0 | 837 | 5.2772 | 0.4667 |
| 0.2402 | 32.0 | 864 | 6.2470 | 0.4222 |
| 0.122 | 33.0 | 891 | 5.2693 | 0.4 |
| 0.2017 | 34.0 | 918 | 6.0732 | 0.5111 |
| 0.0844 | 35.0 | 945 | 6.0091 | 0.5556 |
| 0.1316 | 36.0 | 972 | 6.1584 | 0.4889 |
| 0.0377 | 37.0 | 999 | 7.3245 | 0.4889 |
| 0.1128 | 38.0 | 1026 | 6.6950 | 0.4444 |
| 0.0551 | 39.0 | 1053 | 7.0821 | 0.5111 |
| 0.0382 | 40.0 | 1080 | 7.5961 | 0.4889 |
| 0.0547 | 41.0 | 1107 | 6.2914 | 0.5111 |
| 0.0128 | 42.0 | 1134 | 6.4101 | 0.4889 |
| 0.0359 | 43.0 | 1161 | 6.6377 | 0.5111 |
| 0.004 | 44.0 | 1188 | 6.6707 | 0.4889 |
| 0.0224 | 45.0 | 1215 | 7.0078 | 0.4889 |
| 0.0292 | 46.0 | 1242 | 6.9800 | 0.4889 |
| 0.0156 | 47.0 | 1269 | 6.9010 | 0.4889 |
| 0.0096 | 48.0 | 1296 | 6.9583 | 0.5111 |
| 0.0108 | 49.0 | 1323 | 6.9592 | 0.5111 |
| 0.0394 | 50.0 | 1350 | 6.9592 | 0.5111 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0