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ajtamayoh/
Negation_Scope_Detection_NubEs_Training_Development_mBERT_fine_tuned

Name: Negation_Scope_Detection_NubEs_Training_Development_mBERT_fine_tuned
Availability: InStock

generated_from_trainer

apache-2.0

autotrain_compatible

endpoints_compatible

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Negation_Scope_Detection_NubEs_Training_Development_mBERT_fine_tuned

This model is a fine-tuned version of bert-base-multilingual-cased on NubEs (Training + Development) dataset. It achieves the following results on the evaluation set:

Loss: 0.1712
Precision: 0.8970
Recall: 0.9177
F1: 0.9072
Accuracy: 0.9722

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
num_epochs: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.1805	1.0	1726	0.1542	0.8408	0.8600	0.8503	0.9591
0.126	2.0	3452	0.1271	0.8652	0.8774	0.8713	0.9640
0.0814	3.0	5178	0.1395	0.8715	0.8881	0.8797	0.9662
0.0447	4.0	6904	0.1326	0.8893	0.9068	0.8979	0.9696
0.0247	5.0	8630	0.1805	0.9012	0.9020	0.9016	0.9708
0.0156	6.0	10356	0.1524	0.8972	0.9120	0.9045	0.9706
0.0056	7.0	12082	0.1712	0.8970	0.9177	0.9072	0.9722

Framework versions

Transformers 4.27.3
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2

ajtamayoh/Negation_Scope_Detection_NubEs_Training_Development_mBERT_fine_tuned

Negation_Scope_Detection_NubEs_Training_Development_mBERT_fine_tuned

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

ajtamayoh/
Negation_Scope_Detection_NubEs_Training_Development_mBERT_fine_tuned