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bert-finetuned-ner – AI Model by shubingxl | AlphaNeural AI
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bert-finetuned-ner
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transformers
pytorch
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: 0.4341
Precision: 0.5380
Recall: 0.3216
F1: 0.4026
Accuracy: 0.9367
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
425
0.4089
0.4827
0.2586
0.3368
0.9314
0.2032
2.0
850
0.4356
0.5435
0.2836
0.3727
0.9337
0.0815
3.0
1275
0.4341
0.5380
0.3216
0.4026
0.9367
Framework versions
Transformers 4.34.1
Pytorch 2.0.0+cu117
Datasets 2.14.6
Tokenizers 0.14.1
