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fine-tuned-IndoNLI-data_augmented-with_IndoNLU-Large-V2 – AI Model by muhammadravi251001 | AlphaNeural AI
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fine-tuned-IndoNLI-data_augmented-with_IndoNLU-Large-V2
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transformers
pytorch
tensorboard
bert
text-classification
generated_from_trainer
mit
autotrain_compatible
endpoints_compatible
us
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fine-tuned-IndoNLI-data_augmented-with_IndoNLU-Large-V2
This model is a fine-tuned version of
indobenchmark/indobert-large-p2
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.3044
Accuracy: 0.2
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: 1e-05
train_batch_size: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.06
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.5719
1.0
1
1.3044
0.2
Framework versions
Transformers 4.26.1
Pytorch 1.13.1+cu117
Datasets 2.2.0
Tokenizers 0.13.2
