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_manufacturer_model
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: 0.3394495412844037
car_manufacturer_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: 2.7826
- Accuracy: 0.3394
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: 0.0001
- 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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 7 | 3.1387 | 0.2018 |
| 2.8998 | 2.0 | 14 | 3.1029 | 0.2018 |
| 2.7326 | 3.0 | 21 | 3.0453 | 0.2294 |
| 2.7326 | 4.0 | 28 | 3.0104 | 0.2385 |
| 2.5797 | 5.0 | 35 | 2.9655 | 0.2477 |
| 2.4873 | 6.0 | 42 | 2.9166 | 0.3211 |
| 2.4873 | 7.0 | 49 | 2.9122 | 0.2569 |
| 2.3408 | 8.0 | 56 | 2.8122 | 0.3119 |
| 2.2696 | 9.0 | 63 | 2.8159 | 0.3578 |
| 2.1527 | 10.0 | 70 | 2.8589 | 0.2752 |
| 2.1527 | 11.0 | 77 | 2.8248 | 0.2936 |
| 2.0649 | 12.0 | 84 | 2.7709 | 0.2936 |
| 2.0855 | 13.0 | 91 | 2.8183 | 0.2477 |
| 2.0855 | 14.0 | 98 | 2.7552 | 0.2569 |
| 1.9347 | 15.0 | 105 | 2.7826 | 0.3394 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0