metadata
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- image-classification
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: pokemon-vit
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: pokemon
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.6842105263157895
pokemon-vit
This model is a fine-tuned version of google/vit-base-patch16-224 on the pokemon dataset. It achieves the following results on the evaluation set:
- Loss: 1.2805
- Accuracy: 0.6842
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: 0.0003
- train_batch_size: 16
- 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 10 | 1.8412 | 0.2105 |
| No log | 2.0 | 20 | 1.6505 | 0.3684 |
| No log | 3.0 | 30 | 1.5253 | 0.6316 |
| No log | 4.0 | 40 | 1.4592 | 0.6316 |
| No log | 5.0 | 50 | 1.4373 | 0.6316 |
Framework versions
- Transformers 4.50.0.dev0
- Pytorch 2.6.0
- Datasets 3.2.0
- Tokenizers 0.21.0