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_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: 0.8548696844993141
Boya2_3Class_RMSprop_1e5_20Epoch_Beit-large-224_fold1
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: 1.5790
- Accuracy: 0.8549
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 |
|---|---|---|---|---|
| 0.3103 | 1.0 | 914 | 0.3588 | 0.8494 |
| 0.3671 | 2.0 | 1828 | 0.3382 | 0.8669 |
| 0.2679 | 3.0 | 2742 | 0.4568 | 0.8491 |
| 0.13 | 4.0 | 3656 | 0.7675 | 0.8595 |
| 0.0539 | 5.0 | 4570 | 1.0063 | 0.8543 |
| 0.0034 | 6.0 | 5484 | 1.3345 | 0.8543 |
| 0.001 | 7.0 | 6398 | 1.4146 | 0.8562 |
| 0.0013 | 8.0 | 7312 | 1.6343 | 0.8529 |
| 0.0023 | 9.0 | 8226 | 1.5956 | 0.8486 |
| 0.0001 | 10.0 | 9140 | 1.5790 | 0.8549 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2