PubMedBert-abstract-cord19 – AI Model by pritamdeka | AlphaNeural AI

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PubMedBert-abstract-cord19

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pubmedbert-abstract-cord19

This model is a fine-tuned version of microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext on the pritamdeka/cord-19-abstract dataset. It achieves the following results on the evaluation set:

Loss: 1.3005

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: 5e-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_steps: 10000
num_epochs: 3.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
1.3774	0.15	5000	1.3212
1.3937	0.29	10000	1.4059
1.6812	0.44	15000	1.6174
1.4712	0.59	20000	1.4383
1.4293	0.73	25000	1.4356
1.4155	0.88	30000	1.4283
1.3963	1.03	35000	1.4135
1.3718	1.18	40000	1.3948
1.369	1.32	45000	1.3961
1.354	1.47	50000	1.3788
1.3399	1.62	55000	1.3866
1.3289	1.76	60000	1.3630
1.3155	1.91	65000	1.3609
1.2976	2.06	70000	1.3489
1.2783	2.2	75000	1.3333
1.2696	2.35	80000	1.3260
1.2607	2.5	85000	1.3232
1.2547	2.64	90000	1.3034
1.2495	2.79	95000	1.3035
1.2404	2.94	100000	1.3029

Framework versions

Transformers 4.17.0.dev0
Pytorch 1.10.0+cu111
Datasets 1.18.3
Tokenizers 0.11.0