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PubMedBERT-base-abstract-LitCovid-v1.0 – AI Model by sofia-todeschini | AlphaNeural AI
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sofia-todeschini
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PubMedBERT-base-abstract-LitCovid-v1.0
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transformers
pytorch
tensorboard
bert
text-classification
generated_from_trainer
mit
autotrain_compatible
endpoints_compatible
us
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PubMedBERT-base-abstract-LitCovid-v1.0
This model is a fine-tuned version of
microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.1046
F1: 0.9006
Roc Auc: 0.9352
Accuracy: 0.7996
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: 1
Training results
Training Loss
Epoch
Step
Validation Loss
F1
Roc Auc
Accuracy
0.1105
1.0
3120
0.1046
0.9006
0.9352
0.7996
Framework versions
Transformers 4.28.0
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3
