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nerugm-base – AI Model by apwic | AlphaNeural AI
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apwic
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nerugm-base
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transformers
tensorboard
safetensors
bert
generated_from_trainer
id
indolem/indobert-base-uncased
finetune
mit
endpoints_compatible
us
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nerugm-base
This model is a fine-tuned version of
indolem/indobert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.1575
Precision: 0.7765
Recall: 0.8884
F1: 0.8287
Accuracy: 0.9632
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: 5e-05
train_batch_size: 16
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1.0
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.226
1.0
528
0.1575
0.7765
0.8884
0.8287
0.9632
Framework versions
Transformers 4.39.3
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.15.2
