metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: car-countries-classification
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.29411764705882354
car-countries-classification
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: 1.4039
- Accuracy: 0.2941
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.9231 | 3 | 1.5830 | 0.3137 |
| No log | 1.8462 | 6 | 1.5342 | 0.2941 |
| No log | 2.7692 | 9 | 1.4845 | 0.2941 |
| 1.5308 | 4.0 | 13 | 1.4705 | 0.2745 |
| 1.5308 | 4.9231 | 16 | 1.4534 | 0.3137 |
| 1.5308 | 5.8462 | 19 | 1.4583 | 0.2745 |
| 1.3601 | 6.7692 | 22 | 1.4218 | 0.2941 |
| 1.3601 | 8.0 | 26 | 1.4283 | 0.2745 |
| 1.3601 | 8.9231 | 29 | 1.3973 | 0.3137 |
| 1.2778 | 9.2308 | 30 | 1.4039 | 0.2941 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1