layoutlmv3-final-v1 – AI Model by noavm | AlphaNeural AI

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noavm/
layoutlmv3-final-v1

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token-classification

generated_from_trainer

cc-by-nc-sa-4.0

autotrain_compatible

endpoints_compatible

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layoutlmv3-final-v1

This model is a fine-tuned version of microsoft/layoutlmv3-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0822
Precision: 0.9789
Recall: 0.9839
F1: 0.9814
Accuracy: 0.9852

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
training_steps: 1000

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	2.56	100	1.7056	0.4839	0.5464	0.5133	0.6494
No log	5.13	200	0.4856	0.8255	0.8821	0.8528	0.9217
No log	7.69	300	0.2319	0.9027	0.9355	0.9188	0.9575
No log	10.26	400	0.1437	0.9652	0.9778	0.9715	0.9800
0.9248	12.82	500	0.1204	0.967	0.9748	0.9709	0.9770
0.9248	15.38	600	0.1025	0.9711	0.9808	0.9759	0.9790
0.9248	17.95	700	0.0971	0.9789	0.9829	0.9809	0.9826
0.9248	20.51	800	0.0885	0.9819	0.9849	0.9834	0.9846
0.9248	23.08	900	0.0858	0.9789	0.9839	0.9814	0.9857
0.0697	25.64	1000	0.0822	0.9789	0.9839	0.9814	0.9852

Framework versions

Transformers 4.30.0.dev0
Pytorch 1.8.0+cu101
Datasets 2.12.0
Tokenizers 0.13.3