platzi-vit-model-Joaquin-Romero

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

• Loss: 0.0613
• Accuracy: 0.9850

Model description

It's a Image Classification model performed

Intended uses & limitations

None

Training and evaluation data

Beans dataset

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0002
• train_batch_size: 8
• eval_batch_size: 8
• 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
0.1475	3.85	500	0.0613	0.9850

Framework versions

• Transformers 4.27.1
• Pytorch 1.13.1+cu116
• Datasets 2.10.1
• Tokenizers 0.13.2