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bert-small-finetuned-ner-to-multilabel-wnut-17 – AI Model by muhtasham | AlphaNeural AI
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muhtasham
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bert-small-finetuned-ner-to-multilabel-wnut-17
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transformers
pytorch
tensorboard
safetensors
bert
text-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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bert-small-finetuned-ner-to-multilabel-wnut-17
This model is a fine-tuned version of
google/bert_uncased_L-4_H-512_A-8
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.2186
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: 3e-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: constant
num_epochs: 20
Training results
Training Loss
Epoch
Step
Validation Loss
0.1987
1.18
500
0.2114
0.1235
2.35
1000
0.1894
0.0924
3.53
1500
0.1890
0.0735
4.71
2000
0.1958
0.0534
5.88
2500
0.1993
0.0401
7.06
3000
0.2186
Framework versions
Transformers 4.21.2
Pytorch 1.12.1+cu113
Datasets 2.4.0
Tokenizers 0.12.1
