results – AI Model by nishhaaann | AlphaNeural AI

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nishhaaann/
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text-classification

generated_from_trainer

medicalai/ClinicalBERT

autotrain_compatible

endpoints_compatible

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results

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

Loss: 0.8614
Accuracy: 0.6145
Precision: 0.6243
Recall: 0.6145
F1: 0.5971
Roc Auc: 0.8073

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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Roc Auc
No log	1.0	42	1.0433	0.4458	0.4351	0.4458	0.3685	0.7162
No log	2.0	84	0.8946	0.5663	0.5641	0.5663	0.5559	0.7823
No log	3.0	126	0.9142	0.5783	0.6385	0.5783	0.5332	0.7896
No log	4.0	168	0.8497	0.6386	0.6434	0.6386	0.6299	0.8084
No log	5.0	210	0.8614	0.6145	0.6243	0.6145	0.5971	0.8073

Framework versions

Transformers 4.46.3
Pytorch 2.5.1+cu121
Datasets 2.14.5
Tokenizers 0.20.3