layoutlmv3-large-model2ab-telephone-consultation-discharge – AI Model by neuralit | AlphaNeural AI

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neuralit/
layoutlmv3-large-model2ab-telephone-consultation-discharge

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text-classification

document-classification

medical-documents

generated_from_trainer

microsoft/layoutlmv3-large

cc-by-nc-sa-4.0

endpoints_compatible

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layoutlmv3-large-model2ab-telephone-consultation-discharge

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

Loss: 0.2897
Accuracy: 0.9334
Macro Precision: 0.9333
Macro Recall: 0.9365
Macro F1: 0.9344
Weighted F1: 0.9332
Precision Telephone Encounter: 0.9283
Recall Telephone Encounter: 0.9510
F1 Telephone Encounter: 0.9395
Precision Consultation Note: 0.9439
Recall Consultation Note: 0.8899
F1 Consultation Note: 0.9161
Precision Discharge Report: 0.9277
Recall Discharge Report: 0.9686
F1 Discharge Report: 0.9477

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: 2e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAFACTOR and the args are: No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Macro Precision	Macro Recall	Macro F1	Weighted F1	Precision Telephone Encounter	Recall Telephone Encounter	F1 Telephone Encounter	Precision Consultation Note	Recall Consultation Note	F1 Consultation Note	Precision Discharge Report	Recall Discharge Report	F1 Discharge Report
0.1719	1.4216	500	0.2575	0.9303	0.9332	0.9330	0.9331	0.9303	0.9187	0.9224	0.9206	0.9248	0.9207	0.9227	0.9560	0.9560	0.9560
0.1268	2.8432	1000	0.2906	0.9334	0.9333	0.9365	0.9344	0.9332	0.9283	0.9510	0.9395	0.9439	0.8899	0.9161	0.9277	0.9686	0.9477

Framework versions

Transformers 4.57.6
Pytorch 2.10.0+cu128
Tokenizers 0.22.2