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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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- meteor |
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model-index: |
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- name: distilbart-cnn-12-6-finetuned-1.3.2 |
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results: [] |
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datasets: |
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- ateneoscsl/BUOD_articlescraper |
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- cnn_dailymail |
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- xsum |
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language: |
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- tl |
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- en |
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--- |
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# 📋 BUOD: distilBART Transformer Model |
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[](https://huggingface.co/jamesesguerra/distilbart-cnn-12-6-finetuned-1.3.1) |
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Authors: [James Esguerra](https://huggingface.co/jamesesguerra), [Julia Avila](), [Hazielle Bugayong](https://huggingface.co/0xhaz) |
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This model is a fine-tuned version of [sshleifer/distilbart-cnn-12-6](https://huggingface.co/sshleifer/distilbart-cnn-12-6) on the KAMI-3000 dataset, for the task of Filipino Text Summarization. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8049 |
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- Rouge1: 50.5143 |
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- Rouge2: 23.2481 |
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- Rougel: 34.135 |
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- Rougelsum: 46.4261 |
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## 🔧 Finetuning/ 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: 5e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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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: 2 |
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#### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
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| 2.1377 | 1.0 | 586 | 1.8792 | 49.8737 | 22.7881 | 33.6698 | 45.8037 | |
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| 1.5731 | 2.0 | 1172 | 1.8049 | 50.5143 | 23.2481 | 34.135 | 46.4261 | |
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#### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
