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End of training

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README.md ADDED
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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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+ datasets:
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+ - indonlg
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+ metrics:
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+ - rouge
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+ model-index:
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+ - name: IndoNanoT5-base-Liputan6-Canonical
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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: liputan6_canonical
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+ split: validation
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+ args: liputan6_canonical
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+ metrics:
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+ - name: Rouge1
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+ type: rouge
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+ value: 0.3976
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+ ---
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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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+
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+ # IndoNanoT5-base-Liputan6-Canonical
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+
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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: 1.1194
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+ - Rouge1: 0.3976
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+ - Rouge2: 0.2229
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+ - Rougel: 0.3346
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+ - Rougelsum: 0.3345
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+ - Gen Len: 43.3808
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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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: 50
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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+ |:-------------:|:-----:|:------:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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+ | 0.9693 | 1.0 | 24236 | 1.3245 | 0.3082 | 0.1585 | 0.2687 | 0.2688 | 18.9956 |
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+ | 0.9338 | 2.0 | 48472 | 1.2759 | 0.3105 | 0.159 | 0.2705 | 0.2706 | 18.9985 |
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+ | 0.8632 | 3.0 | 72708 | 1.2698 | 0.3094 | 0.1586 | 0.2701 | 0.2702 | 18.9995 |
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+ | 0.8257 | 4.0 | 96944 | 1.2631 | 0.312 | 0.1603 | 0.2716 | 0.2715 | 18.9993 |
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+ | 0.7789 | 5.0 | 121180 | 1.2642 | 0.3149 | 0.1625 | 0.2748 | 0.2747 | 18.9998 |
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+ | 0.7595 | 6.0 | 145416 | 1.2587 | 0.3202 | 0.1658 | 0.279 | 0.2791 | 18.9995 |
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+ | 0.7343 | 7.0 | 169652 | 1.2644 | 0.3183 | 0.1647 | 0.2773 | 0.2773 | 18.9996 |
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+ | 0.7165 | 8.0 | 193888 | 1.2635 | 0.3141 | 0.1605 | 0.2732 | 0.2732 | 18.9993 |
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+ | 0.6697 | 9.0 | 218124 | 1.2856 | 0.316 | 0.162 | 0.275 | 0.275 | 18.9998 |
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+ | 0.6729 | 10.0 | 242360 | 1.2809 | 0.3195 | 0.164 | 0.2775 | 0.2776 | 18.9992 |
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+ | 0.6471 | 11.0 | 266596 | 1.2833 | 0.3185 | 0.1636 | 0.2769 | 0.277 | 18.9982 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.37.2
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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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+ "transformers_version": "4.37.2"
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