metadata
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Boya1_3Class_Adamax_1e4_20Epoch_Beit-large-224_fold4
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: 0.8420054200542005
Boya1_3Class_Adamax_1e4_20Epoch_Beit-large-224_fold4
This model is a fine-tuned version of microsoft/beit-large-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.7296
- Accuracy: 0.8420
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: 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: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.3707 | 1.0 | 923 | 0.4482 | 0.8136 |
0.3226 | 2.0 | 1846 | 0.4118 | 0.8336 |
0.1875 | 3.0 | 2769 | 0.5879 | 0.8344 |
0.1605 | 4.0 | 3692 | 0.7513 | 0.8304 |
0.1167 | 5.0 | 4615 | 1.2298 | 0.8396 |
0.0003 | 6.0 | 5538 | 1.5337 | 0.8331 |
0.0635 | 7.0 | 6461 | 1.5787 | 0.8377 |
0.0071 | 8.0 | 7384 | 1.6914 | 0.8350 |
0.0 | 9.0 | 8307 | 1.7195 | 0.8404 |
0.0 | 10.0 | 9230 | 1.7296 | 0.8420 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2