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lchiang/
layoutlmv3-finetuned-cord_100

Name: layoutlmv3-finetuned-cord_100
Availability: InStock

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layoutlmv3-finetuned-cord_100

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

Loss: 0.2090
Precision: 0.9465
Recall: 0.9543
F1: 0.9504
Accuracy: 0.9584

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: 5
eval_batch_size: 5
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 2500

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.56	250	1.0347	0.6965	0.7695	0.7312	0.7861
1.4031	3.12	500	0.5641	0.8491	0.8720	0.8604	0.8744
1.4031	4.69	750	0.3899	0.8810	0.9087	0.8946	0.9138
0.4005	6.25	1000	0.3025	0.9202	0.9319	0.9260	0.9355
0.4005	7.81	1250	0.2641	0.9211	0.9349	0.9279	0.9402
0.2161	9.38	1500	0.2406	0.9277	0.9416	0.9346	0.9474
0.2161	10.94	1750	0.2250	0.9343	0.9469	0.9405	0.9516
0.1474	12.5	2000	0.2238	0.9415	0.9513	0.9464	0.9542
0.1474	14.06	2250	0.2128	0.9451	0.9536	0.9493	0.9571
0.1128	15.62	2500	0.2090	0.9465	0.9543	0.9504	0.9584

Framework versions

Transformers 4.30.2
Pytorch 2.0.1
Datasets 2.13.1
Tokenizers 0.13.3

lchiang/layoutlmv3-finetuned-cord_100

layoutlmv3-finetuned-cord_100

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

lchiang/
layoutlmv3-finetuned-cord_100