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bert-finetuned-ner – AI Model by KrishnaSriIpsitMantri | AlphaNeural AI
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KrishnaSriIpsitMantri
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bert-finetuned-ner
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transformers
safetensors
bert
token-classification
generated_from_trainer
wnut_17
google-bert/bert-base-cased
finetune
apache-2.0
model-index
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 wnut_17 dataset. It achieves the following results on the evaluation set:
Loss: 0.3691
Precision: 0.5510
Recall: 0.4007
F1: 0.4640
Accuracy: 0.9174
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: 32
eval_batch_size: 32
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
No log
1.0
107
0.4278
0.5169
0.2380
0.3260
0.9021
No log
2.0
214
0.3786
0.6056
0.3600
0.4516
0.9135
No log
3.0
321
0.3691
0.5510
0.4007
0.4640
0.9174
Framework versions
Transformers 4.48.3
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0
