metadata

library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
  - image-classification
  - vision
  - generated_from_trainer
datasets:
  - arrow
metrics:
  - accuracy
model-index:
  - name: vit-base-beans
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: arrow
          type: arrow
          config: default
          split: validation
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9924812030075187

vit-base-beans

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the arrow dataset. It achieves the following results on the evaluation set:

Loss: 0.0667
Accuracy: 0.9925

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: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 1337
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5.0

Training results

Training Loss	Epoch	Step	Accuracy	Validation Loss
0.2797	1.0	130	0.9624	0.2229
0.1283	2.0	260	0.9774	0.1240
0.1325	3.0	390	0.9774	0.0953
0.0809	4.0	520	0.9925	0.0667
0.1164	5.0	650	0.9774	0.0842

Framework versions

Transformers 4.44.2
Pytorch 2.3.1
Datasets 2.21.0
Tokenizers 0.19.1