metadata
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
- f1
model-index:
- name: got-model
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: 0.9428571428571428
- name: F1
type: f1
value: 0.9442260195944405
got-model
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.1971
- Accuracy: 0.9429
- F1: 0.9442
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: 2e-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
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.073 | 1.0 | 42 | 0.2416 | 0.9238 | 0.9250 |
| 0.061 | 2.0 | 84 | 0.2160 | 0.9333 | 0.9345 |
| 0.0543 | 3.0 | 126 | 0.2114 | 0.9429 | 0.9432 |
| 0.0497 | 4.0 | 168 | 0.2028 | 0.9429 | 0.9442 |
| 0.046 | 5.0 | 210 | 0.1985 | 0.9429 | 0.9442 |
| 0.0435 | 6.0 | 252 | 0.2009 | 0.9429 | 0.9442 |
| 0.0414 | 7.0 | 294 | 0.1976 | 0.9429 | 0.9442 |
| 0.0402 | 8.0 | 336 | 0.1978 | 0.9429 | 0.9442 |
| 0.0391 | 9.0 | 378 | 0.1967 | 0.9429 | 0.9442 |
| 0.0385 | 10.0 | 420 | 0.1971 | 0.9429 | 0.9442 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0