metadata
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Boya3_3Class_RMSprop_1e5_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: 0.8427722772277227
Boya3_3Class_RMSprop_1e5_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: 1.6371
- Accuracy: 0.8428
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 |
|---|---|---|---|---|
| 0.387 | 1.0 | 632 | 0.4262 | 0.8313 |
| 0.2307 | 2.0 | 1264 | 0.4759 | 0.7952 |
| 0.175 | 3.0 | 1896 | 0.5470 | 0.8238 |
| 0.0757 | 4.0 | 2528 | 0.8287 | 0.8388 |
| 0.0394 | 5.0 | 3160 | 1.0981 | 0.8451 |
| 0.0241 | 6.0 | 3792 | 1.2962 | 0.8285 |
| 0.0403 | 7.0 | 4424 | 1.4716 | 0.8325 |
| 0.0001 | 8.0 | 5056 | 1.5920 | 0.8436 |
| 0.0035 | 9.0 | 5688 | 1.6035 | 0.8384 |
| 0.0 | 10.0 | 6320 | 1.6371 | 0.8428 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2