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bert-base-cased-multilingual-finetuned-ner – AI Model by Lukas97 | AlphaNeural AI
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Lukas97
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bert-base-cased-multilingual-finetuned-ner
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transformers
pytorch
tensorboard
bert
token-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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bert-base-cased-multilingual-finetuned-ner
This model is a fine-tuned version of
bert-base-multilingual-cased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0980
Precision: 0.8968
Recall: 0.9288
F1: 0.9125
Accuracy: 0.9687
Model description
bert-base-cased-multlingual-finetuned-ner with striped conll2003 dataset
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
No log
1.0
125
0.2499
0.7530
0.8066
0.7789
0.9369
No log
2.0
250
0.1020
0.8916
0.9211
0.9061
0.9729
No log
3.0
375
0.0980
0.8968
0.9288
0.9125
0.9687
Framework versions
Transformers 4.28.1
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3
