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bert-finetuned-ner – AI Model by Daga2001 | AlphaNeural AI
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Daga2001
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bert-finetuned-ner
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transformers
tensorboard
safetensors
bert
token-classification
generated_from_trainer
conll2002
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 conll2002 dataset. It achieves the following results on the evaluation set:
Loss: 0.1430
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
0.1012
1.0
1041
0.1433
0.0658
2.0
2082
0.1372
0.0414
3.0
3123
0.1430
Framework versions
Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.19.2
Tokenizers 0.19.1
