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_fold5
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: 0.8516790098407223
Karma_3Class_3Class_Adamax_1e4_20Epoch_Beit-large-224_fold5
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: 1.5974
- Accuracy: 0.8517
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 |
|---|---|---|---|---|
| 0.5401 | 1.0 | 2468 | 0.4134 | 0.8245 |
| 0.3613 | 2.0 | 4936 | 0.3769 | 0.8436 |
| 0.2269 | 3.0 | 7404 | 0.4419 | 0.8491 |
| 0.1197 | 4.0 | 9872 | 0.6551 | 0.8550 |
| 0.0481 | 5.0 | 12340 | 0.8909 | 0.8473 |
| 0.0589 | 6.0 | 14808 | 1.0841 | 0.8503 |
| 0.0006 | 7.0 | 17276 | 1.3558 | 0.8503 |
| 0.0 | 8.0 | 19744 | 1.5346 | 0.8485 |
| 0.0299 | 9.0 | 22212 | 1.6012 | 0.8498 |
| 0.0015 | 10.0 | 24680 | 1.5974 | 0.8517 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2