metadata
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Boya2_3Class_RMSprop_1e5_20Epoch_Beit-large-224_fold3
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: 0.8547990155865464
Boya2_3Class_RMSprop_1e5_20Epoch_Beit-large-224_fold3
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: 1.7047
- Accuracy: 0.8548
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4467 | 1.0 | 913 | 0.4441 | 0.8201 |
| 0.3558 | 2.0 | 1826 | 0.3870 | 0.8480 |
| 0.141 | 3.0 | 2739 | 0.6184 | 0.8581 |
| 0.058 | 4.0 | 3652 | 0.8484 | 0.8447 |
| 0.0298 | 5.0 | 4565 | 1.1109 | 0.8551 |
| 0.0004 | 6.0 | 5478 | 1.2544 | 0.8515 |
| 0.0103 | 7.0 | 6391 | 1.5365 | 0.8463 |
| 0.0293 | 8.0 | 7304 | 1.6379 | 0.8553 |
| 0.0 | 9.0 | 8217 | 1.6820 | 0.8575 |
| 0.0001 | 10.0 | 9130 | 1.7047 | 0.8548 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2