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bert-finetuned-hausa_ner – AI Model by peteryushunli | AlphaNeural AI
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bert-finetuned-hausa_ner
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transformers
pytorch
safetensors
bert
token-classification
generated_from_trainer
hausa_voa_ner
google-bert/bert-base-cased
finetune
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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bert-finetuned-hausa_ner
This model is a fine-tuned version of
bert-base-cased
on the hausa_voa_ner dataset. It achieves the following results on the evaluation set:
Loss: 0.1734
Precision: 0.6782
Recall: 0.7763
F1: 0.7239
Accuracy: 0.9516
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
127
0.2162
0.6992
0.7342
0.7163
0.9516
No log
2.0
254
0.1702
0.6900
0.7789
0.7318
0.9518
No log
3.0
381
0.1734
0.6782
0.7763
0.7239
0.9516
Framework versions
Transformers 4.32.0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3
