metadata
license: apache-2.0
base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Boya1_3Class_RMSprop_1-e5_20Epoch_Beit-base-patch16_fold5
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: 0.8310279359913209
Boya1_3Class_RMSprop_1-e5_20Epoch_Beit-base-patch16_fold5
This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k-ft22k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.7877
- Accuracy: 0.8310
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: 16
- eval_batch_size: 16
- 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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5804 | 1.0 | 924 | 0.4986 | 0.8004 |
| 0.4299 | 2.0 | 1848 | 0.4370 | 0.8248 |
| 0.2235 | 3.0 | 2772 | 0.4410 | 0.8446 |
| 0.1347 | 4.0 | 3696 | 0.5720 | 0.8343 |
| 0.0488 | 5.0 | 4620 | 0.8207 | 0.8275 |
| 0.2009 | 6.0 | 5544 | 1.0317 | 0.8329 |
| 0.0566 | 7.0 | 6468 | 1.3823 | 0.8205 |
| 0.0733 | 8.0 | 7392 | 1.3466 | 0.8324 |
| 0.0357 | 9.0 | 8316 | 1.3267 | 0.8362 |
| 0.071 | 10.0 | 9240 | 1.5459 | 0.8264 |
| 0.0505 | 11.0 | 10164 | 1.6231 | 0.8280 |
| 0.1165 | 12.0 | 11088 | 1.6016 | 0.8297 |
| 0.0243 | 13.0 | 12012 | 1.7023 | 0.8351 |
| 0.0327 | 14.0 | 12936 | 1.6673 | 0.8354 |
| 0.002 | 15.0 | 13860 | 1.7768 | 0.8259 |
| 0.0008 | 16.0 | 14784 | 1.8057 | 0.8302 |
| 0.0117 | 17.0 | 15708 | 1.8092 | 0.8253 |
| 0.024 | 18.0 | 16632 | 1.7701 | 0.8324 |
| 0.0349 | 19.0 | 17556 | 1.7881 | 0.8291 |
| 0.0001 | 20.0 | 18480 | 1.7877 | 0.8310 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1