APNR-Braincore-V1

Sans1807/APNR-Braincore-V1

APNR-Braincore-V1 is a image-text-to-text model from Sans1807. 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: Sep 30, 2024
Updated: Oct 2, 2024
SHA: 0e0711a0

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Base models

microsoft/trocr-base-str

Model card

From the Hugging Face model README

microsoft/trocr-base-str

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

Loss: 0.1131
Cer: 0.0102
Wer: 0.0601

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: 1e-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: 25
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer	Wer
1.8737	1.0	173	0.5194	0.0668	0.2809
0.3674	2.0	346	0.1408	0.0183	0.1015
0.0907	3.0	519	0.1151	0.0150	0.0821
0.0584	4.0	692	0.0987	0.0140	0.0778
0.0374	5.0	865	0.1041	0.0113	0.0711
0.0237	6.0	1038	0.0988	0.0102	0.0626
0.0172	7.0	1211	0.0981	0.0109	0.0643
0.0177	8.0	1384	0.1019	0.0109	0.0643
0.0134	9.0	1557	0.1080	0.0106	0.0643
0.009	10.0	1730	0.1023	0.0094	0.0567
0.0092	11.0	1903	0.1021	0.0090	0.0558
0.0085	12.0	2076	0.1057	0.0105	0.0635
0.006	13.0	2249	0.1055	0.0107	0.0618
0.006	14.0	2422	0.1066	0.0105	0.0618
0.0046	15.0	2595	0.1110	0.0103	0.0618
0.0038	16.0	2768	0.1093	0.0101	0.0601
0.0028	17.0	2941	0.1095	0.0099	0.0575
0.0026	18.0	3114	0.1095	0.0099	0.0575
0.0021	19.0	3287	0.1088	0.0097	0.0584
0.0017	20.0	3460	0.1127	0.0105	0.0601
0.0014	21.0	3633	0.1127	0.0099	0.0575
0.0015	22.0	3806	0.1129	0.0101	0.0592
0.0008	23.0	3979	0.1132	0.0101	0.0592
0.0008	24.0	4152	0.1132	0.0102	0.0601
0.0006	25.0	4325	0.1131	0.0102	0.0601

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 2.17.0
Tokenizers 0.19.1

Task: Image-Text-to-Text
Library: transformers
Type: vision-encoder-decoder
Created: Sep 30, 2024
Updated: Oct 2, 2024