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bert-finetuned-ner – AI Model by dvquys | AlphaNeural AI
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dvquys
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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 an unknown dataset. It achieves the following results on the evaluation set:
Loss: 2.0194
Precision: 0.0
Recall: 0.0
F1: 0.0
Accuracy: 0.472
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
3
2.1969
0.0
0.0
0.0
0.352
No log
2.0
6
2.0684
0.0
0.0
0.0
0.448
No log
3.0
9
2.0194
0.0
0.0
0.0
0.472
Framework versions
Transformers 4.42.3
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1
