metadata
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: vit-ena24-clase
results: []
vit-ena24-clase
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the ena24_MD dataset. It achieves the following results on the evaluation set:
- Loss: 0.3132
- Accuracy: 0.9321
- F1: 0.8789
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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- 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: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.9153 | 0.1302 | 100 | 1.7647 | 0.5725 | 0.4646 |
| 1.2463 | 0.2604 | 200 | 1.1008 | 0.7641 | 0.6933 |
| 0.884 | 0.3906 | 300 | 0.9143 | 0.7832 | 0.7113 |
| 0.6852 | 0.5208 | 400 | 0.6161 | 0.8649 | 0.8027 |
| 0.5318 | 0.6510 | 500 | 0.4691 | 0.8947 | 0.8376 |
| 0.5544 | 0.7812 | 600 | 0.3783 | 0.9153 | 0.8984 |
| 0.2321 | 0.9115 | 700 | 0.3132 | 0.9321 | 0.8789 |
Framework versions
- Transformers 4.55.0
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.4