intanm / bri_topic_modeling_baseline_30_001

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Total runs: 10
24-hour runs: 0
7-day runs: 2
30-day runs: 4
Model's Last Updated: July 30 2023
text-classification

Introduction of bri_topic_modeling_baseline_30_001

Model Details of bri_topic_modeling_baseline_30_001

bri_topic_modeling_baseline_30_001

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: 0.8029
  • Accuracy: 0.7748
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: 2
Training results
Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 223 0.9959 0.7284
No log 2.0 446 0.8029 0.7748
Framework versions
  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.1
  • Tokenizers 0.13.3

Runs of intanm bri_topic_modeling_baseline_30_001 on huggingface.co

10
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0
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3-day runs
2
7-day runs
4
30-day runs

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bri_topic_modeling_baseline_30_001 install

bri_topic_modeling_baseline_30_001 is an open source model from GitHub that offers a free installation service, and any user can find bri_topic_modeling_baseline_30_001 on GitHub to install. At the same time, huggingface.co provides the effect of bri_topic_modeling_baseline_30_001 install, users can directly use bri_topic_modeling_baseline_30_001 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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