metadata
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Karma_3Class_3Class_Adamax_1e4_20Epoch_Beit-large-224_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: 0.8534020827014458
Karma_3Class_3Class_Adamax_1e4_20Epoch_Beit-large-224_fold2
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: 1.5433
- Accuracy: 0.8534
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 |
|---|---|---|---|---|
| 0.3595 | 1.0 | 2466 | 0.4309 | 0.8251 |
| 0.3101 | 2.0 | 4932 | 0.3865 | 0.8447 |
| 0.1826 | 3.0 | 7398 | 0.4588 | 0.8485 |
| 0.1658 | 4.0 | 9864 | 0.5997 | 0.8504 |
| 0.1373 | 5.0 | 12330 | 0.8549 | 0.8498 |
| 0.0639 | 6.0 | 14796 | 1.1026 | 0.8527 |
| 0.0234 | 7.0 | 17262 | 1.2762 | 0.8538 |
| 0.0001 | 8.0 | 19728 | 1.4347 | 0.8547 |
| 0.0 | 9.0 | 22194 | 1.5139 | 0.8518 |
| 0.0002 | 10.0 | 24660 | 1.5433 | 0.8534 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2