trocr-ur-v2 – AI Model by mohammadalihumayun | AlphaNeural AI

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mohammadalihumayun/
trocr-ur-v2

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vision-encoder-decoder

generated_from_trainer

cxfajar197/urdu-ocr

endpoints_compatible

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trocr for Urdu

This model is a fine-tuned version of cxfajar197/urdu-ocr on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 2.2939
Cer: 0.2622

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: 2
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
0.2374	0.1594	1000	2.4320	0.3063
0.2788	0.3188	2000	2.3795	0.3029
0.2845	0.4782	3000	2.3814	0.2694
0.2793	0.6377	4000	2.2703	0.2676
0.2735	0.7971	5000	2.2114	0.3016
0.2739	0.9565	6000	2.2326	0.3004
0.1781	1.1159	7000	2.2932	0.2810
0.1392	1.2753	8000	2.3545	0.2828
0.1252	1.4347	9000	2.3462	0.2515
0.1212	1.5941	10000	2.3429	0.2493
0.1172	1.7535	11000	2.2981	0.2769
0.1091	1.9130	12000	2.2939	0.2622

Framework versions

Transformers 4.45.1
Pytorch 2.4.0
Datasets 3.0.1
Tokenizers 0.20.0