bert-base-multilingual-uncased-finetuned-ner-geocorpus – AI Model by GuiTap | AlphaNeural AI

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GuiTap/
bert-base-multilingual-uncased-finetuned-ner-geocorpus

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token-classification

generated_from_trainer

google-bert/bert-base-multilingual-uncased

autotrain_compatible

endpoints_compatible

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bert-base-multilingual-uncased-finetuned-ner-geocorpus

This model is a fine-tuned version of google-bert/bert-base-multilingual-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1137
Precision: 0.8040
Recall: 0.7863
F1: 0.7951
Accuracy: 0.9678

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: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	276	0.1781	0.6711	0.6469	0.6588	0.9541
0.2543	2.0	552	0.1287	0.7567	0.7875	0.7718	0.9638
0.2543	3.0	828	0.1137	0.8040	0.7863	0.7951	0.9678
0.0868	4.0	1104	0.1205	0.7628	0.8630	0.8098	0.9674
0.0868	5.0	1380	0.1184	0.8093	0.8722	0.8396	0.9722
0.0448	6.0	1656	0.1148	0.7817	0.8943	0.8342	0.9723

Framework versions

Transformers 4.41.1
Pytorch 2.1.2
Datasets 2.19.1
Tokenizers 0.19.1