trocr-base-printed_license_plates_ocr_timestamp

PQAshwin/trocr-base-printed_license_plates_ocr_timestamp

trocr-base-printed_license_plates_ocr_timestamp is a image-text-to-text model from PQAshwin. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Image-Text-to-Text
Library: transformers
Model type: vision-encoder-decoder
Access: Public
Created: Jan 16, 2024
Updated: Jan 16, 2024
SHA: 3fd35d7d

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Base models

microsoft/trocr-base-printed

Model card

From the Hugging Face model README

trocr-base-printed_license_plates_ocr_timestamp

This model is a fine-tuned version of microsoft/trocr-base-printed on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0631
Cer: 0.01

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: 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	Cer
10.4185	1.0	315	0.3811	0.0792
0.5419	2.0	630	0.1693	0.0311
0.5419	3.0	945	0.0963	0.0134
0.0944	4.0	1260	0.0631	0.01

Framework versions

Transformers 4.36.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.0

Task: Image-Text-to-Text
Library: transformers
Type: vision-encoder-decoder
Created: Jan 16, 2024
Updated: Jan 16, 2024