fine-tuned-bert-base-multilingual-uncased-NED – AI Model by aomar85 | AlphaNeural AI

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aomar85/
fine-tuned-bert-base-multilingual-uncased-NED

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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fine-tuned-bert-base-multilingual-uncased-NED

This model is a fine-tuned version of bert-base-multilingual-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.2011
Accuracy: 0.9544
Precision: 0.9526
Recall: 0.9787
F1: 0.9655

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: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.1486	1.0	69088	0.1060	0.9660	0.9805	0.9671	0.9738
0.1429	2.0	138176	0.1431	0.9634	0.9778	0.9657	0.9718
0.1655	3.0	207264	0.1299	0.9592	0.9801	0.9569	0.9683
0.175	4.0	276352	0.2011	0.9544	0.9526	0.9787	0.9655

Framework versions

Transformers 4.19.1
Pytorch 1.11.0+cu113
Datasets 2.2.1
Tokenizers 0.12.1