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--- |
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license: apache-2.0 |
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base_model: LazarusNLP/IndoNanoT5-base |
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tags: |
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- generated_from_trainer |
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language: |
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- ind |
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datasets: |
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- GEM/indonlg |
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metrics: |
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- rouge |
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model-index: |
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- name: LazarusNLP/IndoNanoT5-base-IndoSum |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: indonlg |
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type: indonlg |
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config: indosum |
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split: test |
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args: indosum |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 0.7529 |
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- name: Rouge2 |
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type: rouge |
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value: 0.7123 |
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- name: RougeL |
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type: rouge |
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value: 0.733 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# LazarusNLP/IndoNanoT5-base-IndoSum |
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This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co/LazarusNLP/IndoNanoT5-base) on the indonlg dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1086 |
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- Rouge1: 0.7529 |
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- Rouge2: 0.7123 |
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- Rougel: 0.733 |
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- Rougelsum: 0.733 |
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- Gen Len: 110.0391 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.001 |
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- train_batch_size: 8 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| 0.3004 | 1.0 | 1761 | 0.1682 | 0.258 | 0.2277 | 0.2549 | 0.255 | 19.0 | |
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| 0.1463 | 2.0 | 3522 | 0.1318 | 0.2596 | 0.2305 | 0.2563 | 0.2565 | 19.0 | |
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| 0.095 | 3.0 | 5283 | 0.1272 | 0.2602 | 0.2314 | 0.2571 | 0.257 | 19.0 | |
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| 0.0705 | 4.0 | 7044 | 0.1186 | 0.2622 | 0.2338 | 0.2592 | 0.2592 | 19.0 | |
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| 0.0436 | 5.0 | 8805 | 0.1236 | 0.2625 | 0.2342 | 0.2594 | 0.2596 | 19.0 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.2.0+cu118 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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