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-type-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: 0.47368421052631576
car-type-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: 1.0169
- Accuracy: 0.4737
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 | 0.8 | 1 | 1.1248 | 0.1053 |
| No log | 1.6 | 2 | 1.0913 | 0.3684 |
| No log | 2.4 | 3 | 1.0755 | 0.2632 |
| No log | 4.0 | 5 | 1.0527 | 0.3158 |
| No log | 4.8 | 6 | 1.0419 | 0.4211 |
| No log | 5.6 | 7 | 1.0168 | 0.4737 |
| No log | 6.4 | 8 | 1.0152 | 0.5263 |
| 1.0044 | 8.0 | 10 | 1.0169 | 0.4737 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2