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ner_bert – AI Model by themohal | AlphaNeural AI
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themohal
/
ner_bert
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transformers
pytorch
bert
token-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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ner_bert
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: 0.0058
Precision: 0.5703
Recall: 0.1433
F1: 0.2290
Accuracy: 0.9981
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: 32
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.0113
1.0
1314
0.0058
0.5703
0.1433
0.2290
0.9981
Framework versions
Transformers 4.30.0.dev0
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3
