metadata
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- image-classification
- beans
- no-augmentation
- param gfreezed
- generated_from_trainer
datasets:
- beans
metrics:
- accuracy
model-index:
- name: beans_no_aug_freeze_tens
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: nateraw/beans
type: beans
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8872180451127819
beans_no_aug_freeze_tens
This model is a fine-tuned version of google/vit-base-patch16-224 on the nateraw/beans dataset. It achieves the following results on the evaluation set:
- Loss: 0.4175
- Accuracy: 0.8872
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: 0.0002
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 65 | 0.6381 | 0.8271 |
| 0.8113 | 2.0 | 130 | 0.4886 | 0.8571 |
| 0.8113 | 3.0 | 195 | 0.4306 | 0.8722 |
| 0.5137 | 4.0 | 260 | 0.4175 | 0.8872 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.15.2