metadata
license: apache-2.0
base_model: microsoft/cvt-13
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: cvt-13
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9886363636363636
cvt-13
This model is a fine-tuned version of microsoft/cvt-13 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0361
- Accuracy: 0.9886
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4048 | 1.0 | 327 | 0.2161 | 0.9156 |
| 0.33 | 2.0 | 654 | 0.1320 | 0.9501 |
| 0.3147 | 3.0 | 981 | 0.1060 | 0.9612 |
| 0.2213 | 4.0 | 1309 | 0.0820 | 0.9742 |
| 0.3256 | 5.0 | 1636 | 0.0717 | 0.9750 |
| 0.3207 | 6.0 | 1963 | 0.1062 | 0.9626 |
| 0.2273 | 7.0 | 2290 | 0.0535 | 0.9797 |
| 0.2066 | 8.0 | 2618 | 0.0566 | 0.9817 |
| 0.2162 | 9.0 | 2945 | 0.0459 | 0.9828 |
| 0.2296 | 10.0 | 3272 | 0.0444 | 0.9851 |
| 0.187 | 11.0 | 3599 | 0.0348 | 0.9882 |
| 0.2208 | 12.0 | 3927 | 0.0505 | 0.9848 |
| 0.1855 | 13.0 | 4254 | 0.0371 | 0.9869 |
| 0.1875 | 14.0 | 4581 | 0.0384 | 0.9880 |
| 0.202 | 14.99 | 4905 | 0.0361 | 0.9886 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0