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BERT-finetuned-ner-S800 – AI Model by ViktorDo | AlphaNeural AI
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ViktorDo
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BERT-finetuned-ner-S800
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transformers
pytorch
tensorboard
bert
token-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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BERT-finetuned-ner-S800
This model is a fine-tuned version of
bert-base-cased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0830
Precision: 0.5069
Recall: 0.6662
F1: 0.5758
Accuracy: 0.9706
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
55
0.0873
0.4963
0.5680
0.5298
0.9675
No log
2.0
110
0.0845
0.4948
0.6704
0.5694
0.9693
No log
3.0
165
0.0830
0.5069
0.6662
0.5758
0.9706
Framework versions
Transformers 4.29.2
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3
