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bert-finetuned-ner – AI Model by minea | AlphaNeural AI
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bert-finetuned-ner
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transformers
pytorch
bert
token-classification
generated_from_trainer
google-bert/bert-base-cased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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bert-finetuned-ner
This model is a fine-tuned version of
bert-base-cased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.4546
Precision: 0.6154
Recall: 0.6154
F1: 0.6154
Accuracy: 0.9343
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
4
0.8452
0.2692
0.5385
0.3590
0.8030
No log
2.0
8
0.5577
0.4286
0.4615
0.4444
0.9141
No log
3.0
12
0.4546
0.6154
0.6154
0.6154
0.9343
Framework versions
Transformers 4.34.1
Pytorch 2.1.0+cu118
Datasets 2.14.5
Tokenizers 0.14.1
