metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- beans
metrics:
- accuracy
model-index:
- name: img_class_beans
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: beans
type: beans
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9498069498069498
img_class_beans
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the beans dataset. It achieves the following results on the evaluation set:
- Loss: 0.1818
- Accuracy: 0.9498
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: 143
- 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 |
|---|---|---|---|---|
| 1.0147 | 0.98 | 12 | 0.8254 | 0.8494 |
| 0.7452 | 1.96 | 24 | 0.4785 | 0.9266 |
| 0.452 | 2.94 | 36 | 0.3032 | 0.9344 |
| 0.2861 | 4.0 | 49 | 0.2146 | 0.9459 |
| 0.155 | 4.98 | 61 | 0.1719 | 0.9575 |
| 0.1318 | 5.96 | 73 | 0.1655 | 0.9730 |
| 0.1311 | 6.94 | 85 | 0.1550 | 0.9691 |
| 0.1163 | 8.0 | 98 | 0.1710 | 0.9459 |
| 0.1006 | 8.98 | 110 | 0.1752 | 0.9459 |
| 0.1045 | 9.8 | 120 | 0.1472 | 0.9614 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3