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kdrt_content – AI Model by brescia | AlphaNeural AI
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brescia
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kdrt_content
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transformers
tensorboard
safetensors
bert
text-classification
generated_from_trainer
indobenchmark/indobert-base-p1
finetune
mit
autotrain_compatible
endpoints_compatible
us
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kdrt_content
This model is a fine-tuned version of
indobenchmark/indobert-base-p1
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.2446
Accuracy: 0.9231
Precision: 0.9231
Recall: 0.9231
F1: 0.9231
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: 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: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1
No log
1.0
59
0.4204
0.8291
0.8291
0.8291
0.8291
No log
2.0
118
0.2446
0.9231
0.9231
0.9231
0.9231
Framework versions
Transformers 4.40.0
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.19.1
