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--- |
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language: |
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- id |
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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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datasets: |
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- id_liputan6 |
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metrics: |
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- rouge |
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model-index: |
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- name: liputan6-lora-16 |
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results: |
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- task: |
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name: Summarization |
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type: summarization |
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dataset: |
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name: id_liputan6 canonical |
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type: id_liputan6 |
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config: canonical |
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split: validation |
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args: canonical |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 43.1279 |
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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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# liputan6-lora-16 |
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This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co./LazarusNLP/IndoNanoT5-base) on the id_liputan6 canonical dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2652 |
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- Rouge1: 43.1279 |
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- Rouge2: 34.4893 |
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- Rougel: 39.464 |
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- Rougelsum: 41.6727 |
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- Gen Len: 58.936 |
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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: 16 |
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- eval_batch_size: 32 |
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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: 5.0 |
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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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| 1.2779 | 1.0 | 63 | 0.3734 | 40.6247 | 32.4945 | 37.6262 | 39.2634 | 52.145 | |
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| 0.533 | 2.0 | 126 | 0.2652 | 42.9261 | 34.4419 | 39.4137 | 41.4698 | 53.098 | |
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| 0.4176 | 3.0 | 189 | 0.2285 | 40.0567 | 30.7942 | 36.765 | 38.66 | 50.993 | |
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| 0.364 | 4.0 | 252 | 0.2309 | 42.2149 | 33.065 | 38.5226 | 40.8353 | 55.49 | |
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| 0.3343 | 5.0 | 315 | 0.2211 | 41.3186 | 32.0318 | 37.7094 | 39.8931 | 54.221 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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