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bert-finetuned-unpunctual-text-segmentation-v2 – AI Model by TankuVie | AlphaNeural AI
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bert-finetuned-unpunctual-text-segmentation-v2
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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-v2
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: 0.0010
Precision: 0.9989
Recall: 0.9979
F1: 0.9984
Accuracy: 0.9997
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
0.0047
1.0
4750
0.0041
0.9892
0.9966
0.9929
0.9988
0.0015
2.0
9500
0.0017
0.9983
0.9953
0.9968
0.9995
0.0004
3.0
14250
0.0010
0.9989
0.9979
0.9984
0.9997
Framework versions
Transformers 4.31.0.dev0
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3
