biobert_model – AI Model by fffffly | AlphaNeural AI

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biobert_model

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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biobert_model

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

Loss: 0.9645
Accuracy: 0.8711
F1: 0.8475

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
num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	334	0.6463	0.6897	0.7129
0.4503	2.0	668	0.3590	0.8651	0.8269
0.2715	3.0	1002	0.4549	0.8711	0.8252
0.2715	4.0	1336	0.6012	0.8681	0.8434
0.1335	5.0	1670	0.6307	0.8576	0.8313
0.0746	6.0	2004	0.7658	0.8636	0.8366
0.0746	7.0	2338	0.8658	0.8666	0.8436
0.0307	8.0	2672	0.8312	0.8711	0.8453
0.0148	9.0	3006	0.8922	0.8651	0.8421
0.0148	10.0	3340	0.8761	0.8726	0.8490
0.0128	11.0	3674	0.9329	0.8681	0.8462
0.0105	12.0	4008	0.9512	0.8666	0.8441
0.0105	13.0	4342	0.9553	0.8711	0.8475
0.0069	14.0	4676	0.9731	0.8681	0.8445
0.0046	15.0	5010	0.9645	0.8711	0.8475

Framework versions

Transformers 4.29.2
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3