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_sgd_00001_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: 0.26666666666666666
hushem_1x_beit_base_sgd_00001_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: 1.5467
- Accuracy: 0.2667
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 | 1.5555 | 0.2667 |
| 1.6026 | 2.0 | 12 | 1.5551 | 0.2667 |
| 1.6026 | 3.0 | 18 | 1.5546 | 0.2667 |
| 1.5488 | 4.0 | 24 | 1.5542 | 0.2667 |
| 1.6016 | 5.0 | 30 | 1.5538 | 0.2667 |
| 1.6016 | 6.0 | 36 | 1.5534 | 0.2667 |
| 1.5779 | 7.0 | 42 | 1.5530 | 0.2667 |
| 1.5779 | 8.0 | 48 | 1.5527 | 0.2667 |
| 1.588 | 9.0 | 54 | 1.5523 | 0.2667 |
| 1.5533 | 10.0 | 60 | 1.5519 | 0.2667 |
| 1.5533 | 11.0 | 66 | 1.5516 | 0.2667 |
| 1.5856 | 12.0 | 72 | 1.5513 | 0.2667 |
| 1.5856 | 13.0 | 78 | 1.5510 | 0.2667 |
| 1.5657 | 14.0 | 84 | 1.5507 | 0.2667 |
| 1.5825 | 15.0 | 90 | 1.5503 | 0.2667 |
| 1.5825 | 16.0 | 96 | 1.5501 | 0.2667 |
| 1.5958 | 17.0 | 102 | 1.5498 | 0.2667 |
| 1.5958 | 18.0 | 108 | 1.5495 | 0.2667 |
| 1.578 | 19.0 | 114 | 1.5493 | 0.2667 |
| 1.5925 | 20.0 | 120 | 1.5491 | 0.2667 |
| 1.5925 | 21.0 | 126 | 1.5489 | 0.2667 |
| 1.5804 | 22.0 | 132 | 1.5486 | 0.2667 |
| 1.5804 | 23.0 | 138 | 1.5484 | 0.2667 |
| 1.5969 | 24.0 | 144 | 1.5482 | 0.2667 |
| 1.5643 | 25.0 | 150 | 1.5481 | 0.2667 |
| 1.5643 | 26.0 | 156 | 1.5479 | 0.2667 |
| 1.5656 | 27.0 | 162 | 1.5478 | 0.2667 |
| 1.5656 | 28.0 | 168 | 1.5476 | 0.2667 |
| 1.5441 | 29.0 | 174 | 1.5475 | 0.2667 |
| 1.587 | 30.0 | 180 | 1.5474 | 0.2667 |
| 1.587 | 31.0 | 186 | 1.5473 | 0.2667 |
| 1.5666 | 32.0 | 192 | 1.5472 | 0.2667 |
| 1.5666 | 33.0 | 198 | 1.5471 | 0.2667 |
| 1.5492 | 34.0 | 204 | 1.5470 | 0.2667 |
| 1.5567 | 35.0 | 210 | 1.5469 | 0.2667 |
| 1.5567 | 36.0 | 216 | 1.5469 | 0.2667 |
| 1.5593 | 37.0 | 222 | 1.5468 | 0.2667 |
| 1.5593 | 38.0 | 228 | 1.5468 | 0.2667 |
| 1.5776 | 39.0 | 234 | 1.5468 | 0.2667 |
| 1.5552 | 40.0 | 240 | 1.5467 | 0.2667 |
| 1.5552 | 41.0 | 246 | 1.5467 | 0.2667 |
| 1.5605 | 42.0 | 252 | 1.5467 | 0.2667 |
| 1.5605 | 43.0 | 258 | 1.5467 | 0.2667 |
| 1.6075 | 44.0 | 264 | 1.5467 | 0.2667 |
| 1.5667 | 45.0 | 270 | 1.5467 | 0.2667 |
| 1.5667 | 46.0 | 276 | 1.5467 | 0.2667 |
| 1.5665 | 47.0 | 282 | 1.5467 | 0.2667 |
| 1.5665 | 48.0 | 288 | 1.5467 | 0.2667 |
| 1.5544 | 49.0 | 294 | 1.5467 | 0.2667 |
| 1.5829 | 50.0 | 300 | 1.5467 | 0.2667 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0