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_RMSprop_1e5_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: 0.8576483672025074
Karma_3Class_RMSprop_1e5_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: 1.6418
- Accuracy: 0.8576
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 |
|---|---|---|---|---|
| 0.3343 | 1.0 | 2466 | 0.3772 | 0.8460 |
| 0.269 | 2.0 | 4932 | 0.3610 | 0.8583 |
| 0.1499 | 3.0 | 7398 | 0.4653 | 0.8552 |
| 0.1293 | 4.0 | 9864 | 0.8042 | 0.8496 |
| 0.1824 | 5.0 | 12330 | 0.9597 | 0.8549 |
| 0.1453 | 6.0 | 14796 | 1.2832 | 0.8563 |
| 0.0537 | 7.0 | 17262 | 1.4415 | 0.8533 |
| 0.0 | 8.0 | 19728 | 1.6006 | 0.8561 |
| 0.0 | 9.0 | 22194 | 1.6244 | 0.8587 |
| 0.0 | 10.0 | 24660 | 1.6418 | 0.8576 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2