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README.md
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---
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license: apache-2.0
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tags:
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- summarization
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- generated_from_trainer
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datasets:
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- xlsum
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metrics:
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- rouge
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model-index:
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- name: cos801-802-hf-workshop-mt5-small
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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: xlsum
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type: xlsum
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config: swahili
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split: train
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args: swahili
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metrics:
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- name: Rouge1
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type: rouge
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value: 20.928
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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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# cos801-802-hf-workshop-mt5-small
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the xlsum dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.7998
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- Rouge1: 20.928
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- Rouge2: 6.3239
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- Rougel: 17.4455
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- Rougelsum: 17.4566
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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: 5.6e-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: 1
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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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| 3.844 | 1.0 | 1975 | 2.7998 | 20.928 | 6.3239 | 17.4455 | 17.4566 |
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### Framework versions
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- Transformers 4.23.1
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- Pytorch 1.12.1+cu113
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- Datasets 2.6.1
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- Tokenizers 0.13.1
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