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indobert-finetuned-pos – AI Model by rahmanfadhil | AlphaNeural AI
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indobert-finetuned-pos
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transformers
pytorch
tensorboard
bert
token-classification
generated_from_trainer
indonlu
mit
model-index
autotrain_compatible
endpoints_compatible
us
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indobert-finetuned-pos
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: 0.1762
Precision: 0.9477
Recall: 0.9477
F1: 0.9477
Accuracy: 0.9477
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: 16
eval_batch_size: 16
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
420
0.2238
0.9278
0.9278
0.9278
0.9278
0.3621
2.0
840
0.1806
0.9437
0.9437
0.9437
0.9437
0.1504
3.0
1260
0.1762
0.9477
0.9477
0.9477
0.9477
Framework versions
Transformers 4.25.1
Pytorch 1.13.1+cu116
Datasets 2.8.0
Tokenizers 0.13.2
