metadata
license: apache-2.0
base_model: motheecreator/vit-base-patch16-224-in21k-finetuned
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224-in21k-finetuned
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: image_folder
type: image_folder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8571428571428571
vit-base-patch16-224-in21k-finetuned
This model is a fine-tuned version of motheecreator/vit-base-patch16-224-in21k-finetuned on the image_folder dataset. It achieves the following results on the evaluation set:
- Loss: 0.4353
- Accuracy: 0.8571
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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 | Accuracy | Validation Loss |
|---|---|---|---|---|
| 0.7964 | 1.0 | 798 | 0.7271 | 0.7869 |
| 0.6567 | 2.0 | 1596 | 0.7380 | 0.7539 |
| 0.6842 | 3.0 | 2394 | 0.7837 | 0.6287 |
| 0.5242 | 4.0 | 3192 | 0.7839 | 0.6282 |
| 0.4321 | 5.0 | 3990 | 0.7823 | 0.6423 |
| 0.3129 | 6.0 | 4788 | 0.7838 | 0.6533 |
| 0.4245 | 7.0 | 5586 | 0.4382 | 0.8542 |
| 0.3806 | 8.0 | 6384 | 0.4375 | 0.8531 |
| 0.3112 | 9.0 | 7182 | 0.4372 | 0.8557 |
| 0.2692 | 10.0 | 7980 | 0.4353 | 0.8571 |
Framework versions
- Transformers 4.36.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0