metadata
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_beit_base_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: 0.5348837209302325
hushem_1x_beit_base_adamax_001_fold3
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: 1.8097
- Accuracy: 0.5349
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 |
|---|---|---|---|---|
| No log | 1.0 | 6 | 1.4381 | 0.2326 |
| 2.0527 | 2.0 | 12 | 1.4022 | 0.2558 |
| 2.0527 | 3.0 | 18 | 1.3682 | 0.3256 |
| 1.3782 | 4.0 | 24 | 1.3387 | 0.3953 |
| 1.2679 | 5.0 | 30 | 1.3721 | 0.3256 |
| 1.2679 | 6.0 | 36 | 1.7451 | 0.3488 |
| 1.2756 | 7.0 | 42 | 1.3183 | 0.3953 |
| 1.2756 | 8.0 | 48 | 1.4225 | 0.3023 |
| 1.173 | 9.0 | 54 | 1.4215 | 0.3953 |
| 1.1959 | 10.0 | 60 | 1.4072 | 0.3721 |
| 1.1959 | 11.0 | 66 | 1.4852 | 0.4186 |
| 1.1344 | 12.0 | 72 | 1.4523 | 0.2791 |
| 1.1344 | 13.0 | 78 | 1.4043 | 0.4651 |
| 1.0854 | 14.0 | 84 | 1.3638 | 0.3953 |
| 1.1124 | 15.0 | 90 | 1.4323 | 0.3953 |
| 1.1124 | 16.0 | 96 | 1.4664 | 0.4884 |
| 1.0108 | 17.0 | 102 | 1.5473 | 0.3721 |
| 1.0108 | 18.0 | 108 | 1.2300 | 0.4651 |
| 0.9443 | 19.0 | 114 | 1.2523 | 0.4419 |
| 0.9125 | 20.0 | 120 | 1.4134 | 0.3721 |
| 0.9125 | 21.0 | 126 | 1.1280 | 0.4884 |
| 0.8328 | 22.0 | 132 | 1.1054 | 0.4884 |
| 0.8328 | 23.0 | 138 | 1.6081 | 0.4419 |
| 0.7565 | 24.0 | 144 | 1.0331 | 0.5349 |
| 0.7135 | 25.0 | 150 | 1.6384 | 0.5116 |
| 0.7135 | 26.0 | 156 | 1.9524 | 0.4651 |
| 0.7048 | 27.0 | 162 | 1.1399 | 0.5349 |
| 0.7048 | 28.0 | 168 | 1.0504 | 0.5581 |
| 0.7074 | 29.0 | 174 | 1.0452 | 0.5581 |
| 0.7008 | 30.0 | 180 | 1.4757 | 0.5581 |
| 0.7008 | 31.0 | 186 | 1.0663 | 0.4419 |
| 0.5976 | 32.0 | 192 | 1.0991 | 0.5349 |
| 0.5976 | 33.0 | 198 | 1.5330 | 0.5814 |
| 0.5565 | 34.0 | 204 | 1.1511 | 0.5349 |
| 0.458 | 35.0 | 210 | 1.5836 | 0.5349 |
| 0.458 | 36.0 | 216 | 1.4225 | 0.5581 |
| 0.5542 | 37.0 | 222 | 1.4182 | 0.6047 |
| 0.5542 | 38.0 | 228 | 1.3407 | 0.5581 |
| 0.3706 | 39.0 | 234 | 1.4368 | 0.5581 |
| 0.3087 | 40.0 | 240 | 1.6899 | 0.5814 |
| 0.3087 | 41.0 | 246 | 1.8110 | 0.5116 |
| 0.3001 | 42.0 | 252 | 1.8097 | 0.5349 |
| 0.3001 | 43.0 | 258 | 1.8097 | 0.5349 |
| 0.3061 | 44.0 | 264 | 1.8097 | 0.5349 |
| 0.2986 | 45.0 | 270 | 1.8097 | 0.5349 |
| 0.2986 | 46.0 | 276 | 1.8097 | 0.5349 |
| 0.2791 | 47.0 | 282 | 1.8097 | 0.5349 |
| 0.2791 | 48.0 | 288 | 1.8097 | 0.5349 |
| 0.2908 | 49.0 | 294 | 1.8097 | 0.5349 |
| 0.2986 | 50.0 | 300 | 1.8097 | 0.5349 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0