Create README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- rouge
+- meteor
+model-index:
+- name: distilbart-cnn-12-6-finetuned-1.3.2
+  results: []
+datasets:
+- ateneoscsl/BUOD_articlescraper
+- cnn_dailymail
+- xsum
+language:
+- tl
+- en
+---
+
+# 📋 BUOD: distilBART Transformer Model
+[![Model:distilBART](https://img.shields.io/badge/model-distilBART-green)](https://huggingface.co/jamesesguerra/distilbart-cnn-12-6-finetuned-1.3.1)
+Authors: [James Esguerra](https://huggingface.co/jamesesguerra), [Julia Avila](), [Hazielle Bugayong](https://huggingface.co/0xhaz)
+
+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.
+
+It achieves the following results on the evaluation set:
+- Loss: 1.8049
+- Rouge1: 50.5143
+- Rouge2: 23.2481
+- Rougel: 34.135
+- Rougelsum: 46.4261
+
+## 🔧 Finetuning/ Training procedure
+#### Training hyperparameters
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 2
+
+#### Training results
+| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
+| 2.1377        | 1.0   | 586  | 1.8792          | 49.8737 | 22.7881 | 33.6698 | 45.8037   |
+| 1.5731        | 2.0   | 1172 | 1.8049          | 50.5143 | 23.2481 | 34.135  | 46.4261   |
+
+
+#### Framework versions
+- Transformers 4.25.1
+- Pytorch 1.12.1+cu113
+- Datasets 2.7.1
+- Tokenizers 0.13.2