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clinical-finetuned-AgitationModel – AI Model by Sandeepanie | AlphaNeural AI
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clinical-finetuned-AgitationModel
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transformers
pytorch
tensorboard
bert
text-classification
generated_from_trainer
mit
autotrain_compatible
endpoints_compatible
us
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clinical-finetuned-AgitationModel
This model is a fine-tuned version of
emilyalsentzer/Bio_ClinicalBERT
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.9746
Accuracy: 0.88
Precision: 0.9178
Recall: 0.9178
F1: 0.9178
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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1
0.0949
1.0
50
1.0393
0.85
0.8816
0.9178
0.8993
0.0475
2.0
100
1.0619
0.85
0.8816
0.9178
0.8993
0.0149
3.0
150
0.9746
0.88
0.9178
0.9178
0.9178
Framework versions
Transformers 4.21.2
Pytorch 1.12.1+cu113
Tokenizers 0.12.1
