roman_numerals-digit-classification-2022-09-04

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

  • Loss: 0.7018
  • Accuracy: 0.8333

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: 42
  • 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 Validation Loss Accuracy
1.9053 1.0 289 1.3680 0.7132
1.2788 2.0 578 0.9499 0.7966
1.1232 3.0 867 0.8679 0.7279
1.0373 4.0 1156 0.7324 0.8088
0.9658 5.0 1445 0.7018 0.8333

Framework versions

  • Transformers 4.22.0.dev0
  • Pytorch 1.12.1+cu102
  • Datasets 2.4.0
  • Tokenizers 0.12.1
Downloads last month
19
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.

Evaluation results