metadata
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: finetuned-bangladeshi-traditional-food
results: []
finetuned-bangladeshi-traditional-food
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3157
- Accuracy: 0.9529
- Precision: 0.9560
- Recall: 0.9529
- F1: 0.9538
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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Use 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: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 1.2056 | 1.0 | 48 | 0.9746 | 0.8560 | 0.8761 | 0.8560 | 0.8530 |
| 0.5285 | 2.0 | 96 | 0.5351 | 0.9188 | 0.9236 | 0.9188 | 0.9196 |
| 0.3189 | 3.0 | 144 | 0.3756 | 0.9372 | 0.9386 | 0.9372 | 0.9370 |
| 0.221 | 4.0 | 192 | 0.3157 | 0.9529 | 0.9560 | 0.9529 | 0.9538 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.3