metadata

license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
  - generated_from_trainer
datasets:
  - imagefolder
model-index:
  - name: Rice-Image-Classification-Model
    results: []

Rice-Image-Classification-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:

eval_loss: 0.1592
eval_accuracy: 0.9816
eval_runtime: 34.3485
eval_samples_per_second: 9.491
eval_steps_per_second: 2.387
epoch: 186.0
step: 10788

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: 32
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 200

Framework versions

Transformers 4.34.0
Pytorch 2.1.0
Datasets 2.14.5
Tokenizers 0.14.1