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bert-finetuned-ner – AI Model by CarlosHRdJ | AlphaNeural AI
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CarlosHRdJ
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bert-finetuned-ner
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transformers
tensorboard
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 an unknown dataset. It achieves the following results on the evaluation set:
Loss: nan
Precision: 0.6085
Recall: 0.7622
F1: 0.6768
Accuracy: 0.9635
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
0.2588
1.0
979
nan
0.5327
0.7221
0.6131
0.9543
0.0521
2.0
1958
nan
0.6024
0.7655
0.6743
0.9599
0.028
3.0
2937
nan
0.6085
0.7622
0.6768
0.9635
Framework versions
Transformers 4.39.1
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2
