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: 0.09523809523809523
- name: F1
type: f1
value: 0.016563146997929608
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: nan
- Accuracy: 0.0952
- F1: 0.0166
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.0 | 1.0 | 42 | nan | 0.0952 | 0.0166 |
| 0.0 | 2.0 | 84 | nan | 0.0952 | 0.0166 |
| 0.0 | 3.0 | 126 | nan | 0.0952 | 0.0166 |
| 0.0 | 4.0 | 168 | nan | 0.0952 | 0.0166 |
| 0.0 | 5.0 | 210 | nan | 0.0952 | 0.0166 |
| 0.0 | 6.0 | 252 | nan | 0.0952 | 0.0166 |
| 0.0 | 7.0 | 294 | nan | 0.0952 | 0.0166 |
| 0.0 | 8.0 | 336 | nan | 0.0952 | 0.0166 |
| 0.0 | 9.0 | 378 | nan | 0.0952 | 0.0166 |
| 0.0 | 10.0 | 420 | nan | 0.0952 | 0.0166 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3