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_00001_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: 0.5111111111111111
hushem_1x_beit_base_adamax_00001_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: 1.3147
- 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: 1e-05
- 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 | 1.3169 | 0.4222 |
| 1.2993 | 2.0 | 12 | 1.2806 | 0.4667 |
| 1.2993 | 3.0 | 18 | 1.2579 | 0.4889 |
| 0.9161 | 4.0 | 24 | 1.2167 | 0.4889 |
| 0.7083 | 5.0 | 30 | 1.1786 | 0.5556 |
| 0.7083 | 6.0 | 36 | 1.1207 | 0.5778 |
| 0.5194 | 7.0 | 42 | 1.1521 | 0.4667 |
| 0.5194 | 8.0 | 48 | 1.1594 | 0.4889 |
| 0.4029 | 9.0 | 54 | 1.0967 | 0.5333 |
| 0.2875 | 10.0 | 60 | 1.1131 | 0.5333 |
| 0.2875 | 11.0 | 66 | 1.0617 | 0.5556 |
| 0.2225 | 12.0 | 72 | 1.0697 | 0.5778 |
| 0.2225 | 13.0 | 78 | 1.1375 | 0.5333 |
| 0.1628 | 14.0 | 84 | 1.1927 | 0.5111 |
| 0.1384 | 15.0 | 90 | 1.1635 | 0.5556 |
| 0.1384 | 16.0 | 96 | 1.2191 | 0.5111 |
| 0.1154 | 17.0 | 102 | 1.1629 | 0.5556 |
| 0.1154 | 18.0 | 108 | 1.1505 | 0.5556 |
| 0.0953 | 19.0 | 114 | 1.2116 | 0.5333 |
| 0.0771 | 20.0 | 120 | 1.1885 | 0.5333 |
| 0.0771 | 21.0 | 126 | 1.2166 | 0.5111 |
| 0.0552 | 22.0 | 132 | 1.2643 | 0.5111 |
| 0.0552 | 23.0 | 138 | 1.2478 | 0.5111 |
| 0.0544 | 24.0 | 144 | 1.1768 | 0.5556 |
| 0.0597 | 25.0 | 150 | 1.1020 | 0.5778 |
| 0.0597 | 26.0 | 156 | 1.1318 | 0.5556 |
| 0.0518 | 27.0 | 162 | 1.1807 | 0.5333 |
| 0.0518 | 28.0 | 168 | 1.2523 | 0.5333 |
| 0.0452 | 29.0 | 174 | 1.2755 | 0.5333 |
| 0.0366 | 30.0 | 180 | 1.2279 | 0.5333 |
| 0.0366 | 31.0 | 186 | 1.2089 | 0.5333 |
| 0.037 | 32.0 | 192 | 1.2327 | 0.5333 |
| 0.037 | 33.0 | 198 | 1.2492 | 0.5111 |
| 0.0339 | 34.0 | 204 | 1.2215 | 0.5333 |
| 0.0349 | 35.0 | 210 | 1.2052 | 0.5556 |
| 0.0349 | 36.0 | 216 | 1.2247 | 0.5111 |
| 0.0299 | 37.0 | 222 | 1.2589 | 0.5111 |
| 0.0299 | 38.0 | 228 | 1.2861 | 0.5111 |
| 0.0453 | 39.0 | 234 | 1.2942 | 0.5111 |
| 0.0256 | 40.0 | 240 | 1.3064 | 0.5111 |
| 0.0256 | 41.0 | 246 | 1.3149 | 0.5111 |
| 0.0285 | 42.0 | 252 | 1.3147 | 0.5111 |
| 0.0285 | 43.0 | 258 | 1.3147 | 0.5111 |
| 0.0329 | 44.0 | 264 | 1.3147 | 0.5111 |
| 0.0329 | 45.0 | 270 | 1.3147 | 0.5111 |
| 0.0329 | 46.0 | 276 | 1.3147 | 0.5111 |
| 0.0305 | 47.0 | 282 | 1.3147 | 0.5111 |
| 0.0305 | 48.0 | 288 | 1.3147 | 0.5111 |
| 0.0327 | 49.0 | 294 | 1.3147 | 0.5111 |
| 0.0227 | 50.0 | 300 | 1.3147 | 0.5111 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0