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_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: 0.8232432432432433
Boya1_3Class_RMSprop_1-e5_20Epoch_Beit-base-patch16_fold2
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: 1.7644
- Accuracy: 0.8232
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 |
|---|---|---|---|---|
| 0.4974 | 1.0 | 923 | 0.5529 | 0.7873 |
| 0.4125 | 2.0 | 1846 | 0.4400 | 0.8268 |
| 0.2808 | 3.0 | 2769 | 0.5196 | 0.8368 |
| 0.1527 | 4.0 | 3692 | 0.5655 | 0.8330 |
| 0.1865 | 5.0 | 4615 | 0.8608 | 0.8173 |
| 0.0741 | 6.0 | 5538 | 1.0784 | 0.8203 |
| 0.0819 | 7.0 | 6461 | 1.3435 | 0.8214 |
| 0.0017 | 8.0 | 7384 | 1.5429 | 0.8286 |
| 0.1022 | 9.0 | 8307 | 1.5116 | 0.8186 |
| 0.0532 | 10.0 | 9230 | 1.6291 | 0.8216 |
| 0.062 | 11.0 | 10153 | 1.6075 | 0.8227 |
| 0.0034 | 12.0 | 11076 | 1.6033 | 0.8278 |
| 0.0602 | 13.0 | 11999 | 1.6450 | 0.83 |
| 0.0052 | 14.0 | 12922 | 1.7169 | 0.8241 |
| 0.0005 | 15.0 | 13845 | 1.7681 | 0.8241 |
| 0.0002 | 16.0 | 14768 | 1.7020 | 0.8308 |
| 0.0 | 17.0 | 15691 | 1.7773 | 0.8286 |
| 0.0465 | 18.0 | 16614 | 1.7601 | 0.8249 |
| 0.0 | 19.0 | 17537 | 1.7672 | 0.8276 |
| 0.0006 | 20.0 | 18460 | 1.7644 | 0.8232 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1