rorshark-vit-base

By amunchet

🎯 Task: Image Classification⚖️ apache-2.0📦 transformers

Model Card

rorshark-vit-base

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: 0.0393
  • Accuracy: 0.9923

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 LossEpochStepValidation LossAccuracy
0.05971.03680.05460.9865
0.20092.07360.05310.9865
0.01143.011040.04180.9904
0.09984.014720.04250.9904
0.12445.018400.03930.9923

Framework versions

  • Transformers 4.36.0.dev0
  • Pytorch 2.1.1+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0

Architecture & Tags

transformerstensorboardsafetensorsvitimage-classificationvisiongenerated_from_trainerbase_model:google/vit-base-patch16-224-in21kbase_model:finetune:google/vit-base-patch16-224-in21kmodel-indexendpoints_compatibleregion:us