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bert-ner-conll2003 – AI Model by claudiaspseabra-ua | AlphaNeural AI
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bert-ner-conll2003
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safetensors
bert
generated_from_trainer
conll2003
google-bert/bert-base-cased
finetune
apache-2.0
us
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bert-ner-conll2003
This model is a fine-tuned version of
bert-base-cased
on the conll2003 dataset. It achieves the following results on the evaluation set:
Loss: 0.7393
Precision: 0.9421
Recall: 0.9490
F1: 0.9455
Accuracy: 0.9907
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: 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
2.673
1.0
878
0.7181
0.9255
0.9336
0.9296
0.9886
0.4519
2.0
1756
0.7564
0.9396
0.9427
0.9411
0.9899
0.2646
3.0
2634
0.7393
0.9421
0.9490
0.9455
0.9907
Framework versions
Transformers 4.36.0
Pytorch 2.10.0+cu128
Datasets 2.16.0
Tokenizers 0.15.2
