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metadata
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
  - generated_from_trainer
language:
  - ind
datasets:
  - GEM/indonlg
metrics:
  - rouge
model-index:
  - name: LazarusNLP/IndoNanoT5-base-IndoSum
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: indonlg
          type: indonlg
          config: indosum
          split: test
          args: indosum
        metrics:
          - name: Rouge1
            type: rouge
            value: 0.7529
          - name: Rouge2
            type: rouge
            value: 0.7123
          - name: RougeL
            type: rouge
            value: 0.733

LazarusNLP/IndoNanoT5-base-IndoSum

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

  • Loss: 0.1086
  • Rouge1: 0.7529
  • Rouge2: 0.7123
  • Rougel: 0.733
  • Rougelsum: 0.733
  • Gen Len: 110.0391

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: 8
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
0.3004 1.0 1761 0.1682 0.258 0.2277 0.2549 0.255 19.0
0.1463 2.0 3522 0.1318 0.2596 0.2305 0.2563 0.2565 19.0
0.095 3.0 5283 0.1272 0.2602 0.2314 0.2571 0.257 19.0
0.0705 4.0 7044 0.1186 0.2622 0.2338 0.2592 0.2592 19.0
0.0436 5.0 8805 0.1236 0.2625 0.2342 0.2594 0.2596 19.0

Framework versions

  • Transformers 4.36.2
  • Pytorch 2.2.0+cu118
  • Datasets 2.16.1
  • Tokenizers 0.15.1