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bert-finetuned-ner – AI Model by RoxieC | AlphaNeural AI
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RoxieC
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bert-finetuned-ner
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transformers
safetensors
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 the None dataset. It achieves the following results on the evaluation set:
Loss: 0.2320
Precision: 0.5229
Recall: 0.3167
F1: 0.3945
Accuracy: 0.9354
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
425
0.2171
0.5069
0.2370
0.3230
0.9294
0.1213
2.0
850
0.2355
0.5404
0.2787
0.3677
0.9332
0.0472
3.0
1275
0.2320
0.5229
0.3167
0.3945
0.9354
Framework versions
Transformers 4.35.0
Pytorch 2.1.0
Datasets 2.14.6
Tokenizers 0.14.1
