Disease_Identification_SonatafyAI_BERT_v1 – AI Model by ajtamayoh | AlphaNeural AI

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ajtamayoh/
Disease_Identification_SonatafyAI_BERT_v1

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token-classification

generated_from_trainer

google-bert/bert-base-cased

autotrain_compatible

endpoints_compatible

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Disease_Identification_SonatafyAI_BERT_v1

This model is a fine-tuned version of google-bert/bert-base-cased on the ncbi_disease dataset. It achieves the following results on the evaluation set:

Loss: 0.1063
Precision: 0.8247
Recall: 0.8729
F1: 0.8481
Accuracy: 0.9840

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.1208	1.0	680	0.0579	0.7339	0.8272	0.7778	0.9816
0.0438	2.0	1360	0.0616	0.7785	0.8755	0.8242	0.9836
0.0171	3.0	2040	0.0736	0.7949	0.8272	0.8107	0.9822
0.0096	4.0	2720	0.0857	0.8173	0.8640	0.8400	0.9844
0.0069	5.0	3400	0.0986	0.8050	0.8551	0.8293	0.9833
0.0016	6.0	4080	0.1055	0.8068	0.8755	0.8397	0.9834
0.0009	7.0	4760	0.1063	0.8247	0.8729	0.8481	0.9840

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2