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bert-base-uncased-finetuned-ner – AI Model by ArBert | AlphaNeural AI
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ArBert
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bert-base-uncased-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-uncased-finetuned-ner
This model is a fine-tuned version of
bert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0905
Precision: 0.9068
Recall: 0.9200
F1: 0.9133
Accuracy: 0.9787
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.1266
1.0
1123
0.0952
0.8939
0.8869
0.8904
0.9742
0.0741
2.0
2246
0.0866
0.8936
0.9247
0.9089
0.9774
0.0496
3.0
3369
0.0905
0.9068
0.9200
0.9133
0.9787
Framework versions
Transformers 4.16.2
Pytorch 1.10.0+cu111
Datasets 1.18.3
Tokenizers 0.11.0
