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README.md
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---
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license: apache-2.0
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base_model: google/mt5-base
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tags:
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- generated_from_trainer
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datasets:
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- thaisum
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metrics:
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- rouge
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model-index:
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- name: mt5_thaisum_finetune
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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: thaisum
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type: thaisum
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config: thaisum
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split: validation
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args: thaisum
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metrics:
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- name: Rouge1
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type: rouge
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value: 0.2022
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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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# mt5_thaisum_finetune
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This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the thaisum dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3039
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- Rouge1: 0.2022
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- Rouge2: 0.0808
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- Rougel: 0.2023
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- Rougelsum: 0.2019
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- Gen Len: 18.9995
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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: 0.0002
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- train_batch_size: 2
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- eval_batch_size: 2
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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: 4
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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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| 2.0742 | 1.0 | 5000 | 0.3272 | 0.1713 | 0.0551 | 0.1716 | 0.1714 | 18.9945 |
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| 1.7874 | 2.0 | 10000 | 0.3073 | 0.1943 | 0.0747 | 0.195 | 0.1941 | 18.997 |
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| 1.6341 | 3.0 | 15000 | 0.3035 | 0.2006 | 0.0807 | 0.2007 | 0.2002 | 19.0 |
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| 1.4501 | 4.0 | 20000 | 0.3039 | 0.2022 | 0.0808 | 0.2023 | 0.2019 | 18.9995 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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