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bert-finetuned-unpunctual-text-segmentation – AI Model by TankuVie | AlphaNeural AI
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bert-finetuned-unpunctual-text-segmentation
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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-unpunctual-text-segmentation
This model is a fine-tuned version of
bert-base-multilingual-cased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0007
Precision: 0.9996
Recall: 0.9984
F1: 0.9990
Accuracy: 0.9998
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
0.0023
1.0
11252
0.0017
0.9983
0.9953
0.9968
0.9995
0.0006
2.0
22504
0.0010
0.9994
0.9980
0.9987
0.9998
0.0001
3.0
33756
0.0007
0.9996
0.9984
0.9990
0.9998
Framework versions
Transformers 4.30.1
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3
