metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: violation-classification-bantai-vit-v100ep
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: image_folder
type: image_folder
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8969686033922771
violation-classification-bantai-vit-v100ep
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the image_folder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3011
- Accuracy: 0.8970
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.2596 | 1.0 | 101 | 1.2230 | 0.5615 |
| 0.8527 | 2.0 | 202 | 0.8234 | 0.6840 |
| 0.6375 | 3.0 | 303 | 0.6001 | 0.7846 |
| 0.555 | 4.0 | 404 | 0.5038 | 0.8178 |
| 0.4433 | 5.0 | 505 | 0.4338 | 0.8436 |
| 0.406 | 6.0 | 606 | 0.3765 | 0.8661 |
| 0.3517 | 7.0 | 707 | 0.3466 | 0.8793 |
| 0.312 | 8.0 | 808 | 0.3011 | 0.8970 |
| 0.2842 | 9.0 | 909 | 0.2943 | 0.8961 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6