Edit model card

image_classification

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:

  • Loss: 1.6432
  • Accuracy: 0.3688

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: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 40 1.8982 0.3
No log 2.0 80 1.6882 0.3438
No log 3.0 120 1.6481 0.3812

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.2.0.dev20230906
  • Datasets 2.14.5
  • Tokenizers 0.13.3
Downloads last month
12
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for octava/image_classification

Finetuned
(1693)
this model

Evaluation results