layout3 – AI Model by pedro1111 | AlphaNeural AI

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pedro1111/
layout3

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token-classification

generated_from_trainer

microsoft/layoutlmv3-base

cc-by-nc-sa-4.0

autotrain_compatible

endpoints_compatible

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layout3

This model is a fine-tuned version of microsoft/layoutlmv3-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.6334
Precision: 0.8935
Recall: 0.9131
F1: 0.9032
Accuracy: 0.8586

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: 2
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 1000

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.33	100	0.6874	0.7820	0.8073	0.7944	0.7841
No log	2.67	200	0.4485	0.8321	0.8838	0.8571	0.8474
No log	4.0	300	0.4403	0.8579	0.9086	0.8825	0.8414
No log	5.33	400	0.4593	0.8452	0.9056	0.8743	0.8341
0.5531	6.67	500	0.4881	0.8732	0.9170	0.8946	0.8575
0.5531	8.0	600	0.5332	0.8761	0.9101	0.8928	0.8547
0.5531	9.33	700	0.5910	0.8894	0.9106	0.8999	0.8517
0.5531	10.67	800	0.5914	0.8909	0.9131	0.9019	0.8557
0.5531	12.0	900	0.6127	0.9001	0.9180	0.9090	0.8614
0.1245	13.33	1000	0.6334	0.8935	0.9131	0.9032	0.8586

Framework versions

Transformers 4.32.0
Pytorch 2.0.0+cu118
Datasets 2.17.1
Tokenizers 0.13.2