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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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- wiki_lingua
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metrics:
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- rouge
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model-index:
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- name: wiki_lingua-hi-8-3-5.6e-05-mt5-small-finetuned
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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: wiki_lingua
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type: wiki_lingua
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config: hi
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split: test
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args: hi
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metrics:
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- name: Rouge1
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type: rouge
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value: 1.3405
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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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# wiki_lingua-hi-8-3-5.6e-05-mt5-small-finetuned
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the wiki_lingua dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.4454
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- Rouge1: 1.3405
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- Rouge2: 0.3957
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- Rougel: 1.3311
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- Rougelsum: 1.3354
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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: 8
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- eval_batch_size: 8
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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: 3
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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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| 4.5276 | 1.0 | 841 | 2.5614 | 1.3305 | 0.3186 | 1.3393 | 1.345 |
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| 3.0712 | 2.0 | 1682 | 2.4707 | 1.2656 | 0.2856 | 1.2595 | 1.2631 |
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| 2.9584 | 3.0 | 2523 | 2.4454 | 1.3405 | 0.3957 | 1.3311 | 1.3354 |
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### Framework versions
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- Transformers 4.27.4
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- Pytorch 1.13.0
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- Datasets 2.1.0
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- Tokenizers 0.13.2
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