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NLP-HW5-NerTaggerModel – AI Model by Pedrampd | AlphaNeural AI
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Pedrampd
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NLP-HW5-NerTaggerModel
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transformers
pytorch
tensorboard
bert
token-classification
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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NLP-HW5-NerTaggerModel
This model is a fine-tuned version of
bert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0218
Accuracy: 0.9947
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: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.1891
1.0
878
0.0342
0.9909
0.0377
2.0
1756
0.0218
0.9947
Framework versions
Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3
