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_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: 0.5333333333333333
hushem_1x_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: 3.2742
- Accuracy: 0.5333
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 |
|---|---|---|---|---|
| No log | 1.0 | 6 | 1.4059 | 0.2444 |
| 2.1162 | 2.0 | 12 | 1.4011 | 0.2444 |
| 2.1162 | 3.0 | 18 | 1.4001 | 0.2444 |
| 1.4079 | 4.0 | 24 | 1.4023 | 0.2444 |
| 1.3851 | 5.0 | 30 | 1.3440 | 0.4 |
| 1.3851 | 6.0 | 36 | 1.6621 | 0.2444 |
| 1.3464 | 7.0 | 42 | 1.3490 | 0.2889 |
| 1.3464 | 8.0 | 48 | 1.3162 | 0.2667 |
| 1.2763 | 9.0 | 54 | 1.5389 | 0.2444 |
| 1.2353 | 10.0 | 60 | 1.1918 | 0.5111 |
| 1.2353 | 11.0 | 66 | 1.2702 | 0.3111 |
| 1.1503 | 12.0 | 72 | 1.1819 | 0.4667 |
| 1.1503 | 13.0 | 78 | 1.1946 | 0.4 |
| 1.1428 | 14.0 | 84 | 1.2858 | 0.4222 |
| 0.9448 | 15.0 | 90 | 1.2191 | 0.5333 |
| 0.9448 | 16.0 | 96 | 1.0792 | 0.4667 |
| 0.8793 | 17.0 | 102 | 1.0942 | 0.5333 |
| 0.8793 | 18.0 | 108 | 1.0695 | 0.5333 |
| 0.7925 | 19.0 | 114 | 1.5298 | 0.4889 |
| 0.7637 | 20.0 | 120 | 1.4292 | 0.4889 |
| 0.7637 | 21.0 | 126 | 1.1665 | 0.4889 |
| 0.6936 | 22.0 | 132 | 1.2681 | 0.4444 |
| 0.6936 | 23.0 | 138 | 1.4911 | 0.4667 |
| 0.6862 | 24.0 | 144 | 1.6737 | 0.4889 |
| 0.6196 | 25.0 | 150 | 1.3333 | 0.5111 |
| 0.6196 | 26.0 | 156 | 2.1751 | 0.4889 |
| 0.5849 | 27.0 | 162 | 1.6904 | 0.4444 |
| 0.5849 | 28.0 | 168 | 2.4209 | 0.5333 |
| 0.5413 | 29.0 | 174 | 1.3664 | 0.4444 |
| 0.4937 | 30.0 | 180 | 2.0398 | 0.5111 |
| 0.4937 | 31.0 | 186 | 1.5682 | 0.5111 |
| 0.4704 | 32.0 | 192 | 2.0516 | 0.5556 |
| 0.4704 | 33.0 | 198 | 2.7441 | 0.5778 |
| 0.4133 | 34.0 | 204 | 2.2801 | 0.5111 |
| 0.354 | 35.0 | 210 | 2.5861 | 0.5333 |
| 0.354 | 36.0 | 216 | 2.6593 | 0.5333 |
| 0.3074 | 37.0 | 222 | 2.7263 | 0.5333 |
| 0.3074 | 38.0 | 228 | 2.8622 | 0.4889 |
| 0.2263 | 39.0 | 234 | 3.1445 | 0.5556 |
| 0.2656 | 40.0 | 240 | 3.2265 | 0.5333 |
| 0.2656 | 41.0 | 246 | 3.2774 | 0.5333 |
| 0.2527 | 42.0 | 252 | 3.2742 | 0.5333 |
| 0.2527 | 43.0 | 258 | 3.2742 | 0.5333 |
| 0.2167 | 44.0 | 264 | 3.2742 | 0.5333 |
| 0.2791 | 45.0 | 270 | 3.2742 | 0.5333 |
| 0.2791 | 46.0 | 276 | 3.2742 | 0.5333 |
| 0.2024 | 47.0 | 282 | 3.2742 | 0.5333 |
| 0.2024 | 48.0 | 288 | 3.2742 | 0.5333 |
| 0.2259 | 49.0 | 294 | 3.2742 | 0.5333 |
| 0.2149 | 50.0 | 300 | 3.2742 | 0.5333 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0