apwic / indosum-seq_bn-rf64-0

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Model's Last Updated: July 22 2024

Introduction of indosum-seq_bn-rf64-0

Model Details of indosum-seq_bn-rf64-0

indosum-seq_bn-rf64-0

This model is a fine-tuned version of LazarusNLP/IndoNanoT5-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5046
  • Rouge1: 72.7451
  • Rouge2: 65.6426
  • Rougel: 69.7965
  • Rougelsum: 71.8443
  • Gen Len: 103.1187
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: 0.001
  • train_batch_size: 16
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5.0
Training results
Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
0.8386 1.0 892 0.5658 68.0586 60.6185 65.0879 67.0846 102.556
0.646 2.0 1784 0.5346 69.6096 62.3885 66.6327 68.7343 107.088
0.6031 3.0 2676 0.5019 70.498 63.0668 67.3204 69.5075 101.6693
0.5753 4.0 3568 0.5093 71.6759 64.4776 68.7095 70.7692 104.52
0.5551 5.0 4460 0.5046 72.0617 64.9137 69.0991 71.1205 102.5733
Framework versions
  • Transformers 4.40.2
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1

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More Information About indosum-seq_bn-rf64-0 huggingface.co Model

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indosum-seq_bn-rf64-0 huggingface.co

indosum-seq_bn-rf64-0 huggingface.co is an AI model on huggingface.co that provides indosum-seq_bn-rf64-0's model effect (), which can be used instantly with this apwic indosum-seq_bn-rf64-0 model. huggingface.co supports a free trial of the indosum-seq_bn-rf64-0 model, and also provides paid use of the indosum-seq_bn-rf64-0. Support call indosum-seq_bn-rf64-0 model through api, including Node.js, Python, http.

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indosum-seq_bn-rf64-0 install

indosum-seq_bn-rf64-0 is an open source model from GitHub that offers a free installation service, and any user can find indosum-seq_bn-rf64-0 on GitHub to install. At the same time, huggingface.co provides the effect of indosum-seq_bn-rf64-0 install, users can directly use indosum-seq_bn-rf64-0 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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