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bert-finetuned-cross-ner-v4 – AI Model by P3ps | AlphaNeural AI
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P3ps
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bert-finetuned-cross-ner-v4
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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-cross-ner-v4
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: 0.1777
Precision: 0.8300
Recall: 0.8637
F1: 0.8465
Accuracy: 0.9560
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
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.2044
1.0
2607
0.1963
0.7779
0.8180
0.7975
0.9459
0.124
2.0
5214
0.1713
0.8158
0.8527
0.8338
0.9546
0.0818
3.0
7821
0.1777
0.8300
0.8637
0.8465
0.9560
Framework versions
Transformers 4.28.0
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3
