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bert-finetuned-ner – AI Model by IvoSchols | AlphaNeural AI
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IvoSchols
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bert-finetuned-ner
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transformers
pytorch
bert
token-classification
generated_from_trainer
google-bert/bert-base-cased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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bert-finetuned-ner
This model is a fine-tuned version of
bert-base-cased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.4003
Precision: 0.5385
Recall: 0.2063
F1: 0.2983
Accuracy: 0.9405
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: 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
385
0.3522
0.5717
0.1175
0.1949
0.9353
0.1984
2.0
770
0.3887
0.5670
0.1904
0.2850
0.9395
0.0884
3.0
1155
0.4003
0.5385
0.2063
0.2983
0.9405
Framework versions
Transformers 4.34.1
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1
