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indobert-sentiment-analysis – AI Model by rikidharmawan | AlphaNeural AI
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indobert-sentiment-analysis
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transformers
tensorboard
safetensors
bert
text-classification
generated_from_trainer
indonlu
indobenchmark/indobert-base-p2
finetune
mit
model-index
autotrain_compatible
endpoints_compatible
us
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indobert-sentiment-analysis
This model is a fine-tuned version of
indobenchmark/indobert-base-p2
on the indonlu dataset. It achieves the following results on the evaluation set:
Loss: 0.3210
Accuracy: 0.916
F1: 0.8879
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: 64
eval_batch_size: 64
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5
Training results
Framework versions
Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1
