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bert-finetuned-ner – AI Model by MPRaveau | AlphaNeural AI
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MPRaveau
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bert-finetuned-ner
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safetensors
bert
generated_from_trainer
google-bert/bert-base-cased
finetune
apache-2.0
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: 0.2440
Precision: 0.4311
Recall: 0.4246
F1: 0.4278
Accuracy: 0.8954
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
202
0.2465
0.4230
0.3745
0.3973
0.8945
No log
2.0
404
0.2350
0.4477
0.3967
0.4206
0.8990
0.2423
3.0
606
0.2440
0.4311
0.4246
0.4278
0.8954
Framework versions
Transformers 4.43.3
Pytorch 2.3.1+cpu
Datasets 2.20.0
Tokenizers 0.19.1
