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_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: 0.8259571001900624
Boya1_3Class_RMSprop_1-e5_20Epoch_Beit-base-patch16_fold1
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: 1.7955
- Accuracy: 0.8260
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 |
|---|---|---|---|---|
| 0.4439 | 1.0 | 924 | 0.4590 | 0.8091 |
| 0.3875 | 2.0 | 1848 | 0.4469 | 0.8227 |
| 0.2939 | 3.0 | 2772 | 0.5412 | 0.8154 |
| 0.1247 | 4.0 | 3696 | 0.6692 | 0.8213 |
| 0.1513 | 5.0 | 4620 | 0.8256 | 0.8227 |
| 0.1409 | 6.0 | 5544 | 1.1386 | 0.8181 |
| 0.0278 | 7.0 | 6468 | 1.3459 | 0.8189 |
| 0.013 | 8.0 | 7392 | 1.5383 | 0.8175 |
| 0.0037 | 9.0 | 8316 | 1.5542 | 0.8254 |
| 0.0119 | 10.0 | 9240 | 1.6982 | 0.8178 |
| 0.0008 | 11.0 | 10164 | 1.7834 | 0.8178 |
| 0.0799 | 12.0 | 11088 | 1.6908 | 0.8230 |
| 0.0845 | 13.0 | 12012 | 1.7310 | 0.8200 |
| 0.0588 | 14.0 | 12936 | 1.7389 | 0.8235 |
| 0.0004 | 15.0 | 13860 | 1.8086 | 0.8246 |
| 0.0004 | 16.0 | 14784 | 1.8040 | 0.8262 |
| 0.0009 | 17.0 | 15708 | 1.7272 | 0.8243 |
| 0.0021 | 18.0 | 16632 | 1.7738 | 0.8238 |
| 0.0559 | 19.0 | 17556 | 1.8013 | 0.8254 |
| 0.0 | 20.0 | 18480 | 1.7955 | 0.8260 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1