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Dinithi/
CancerTextV3

Name: CancerTextV3
Rating: 2.5 (15 reviews)

generated_from_trainer

autotrain_compatible

endpoints_compatible

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CancerTextV3

This model is a fine-tuned version of dmis-lab/biobert-base-cased-v1.1 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.6660
Accuracy: 0.8658
Precision: 0.8448
Recall: 0.8868
F1: 0.8653

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: 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: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.4603	1.0	600	0.3671	0.8575	0.8056	0.9314	0.8640
0.3208	2.0	1200	0.3296	0.8658	0.8613	0.8628	0.8620
0.2619	3.0	1800	0.4023	0.8667	0.8797	0.8405	0.8596
0.2125	4.0	2400	0.3948	0.8733	0.8459	0.9039	0.8740
0.1789	5.0	3000	0.4971	0.8617	0.8243	0.9091	0.8646
0.1568	6.0	3600	0.5372	0.8633	0.8384	0.8902	0.8636
0.1332	7.0	4200	0.6037	0.865	0.8502	0.8765	0.8632
0.1176	8.0	4800	0.6255	0.8675	0.8430	0.8937	0.8676
0.1043	9.0	5400	0.6479	0.865	0.8434	0.8868	0.8645
0.096	10.0	6000	0.6660	0.8658	0.8448	0.8868	0.8653

Framework versions

Transformers 4.21.2
Pytorch 1.12.1+cu113
Datasets 2.4.0
Tokenizers 0.12.1

Dinithi/CancerTextV3

CancerTextV3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Dinithi/
CancerTextV3