update model card README.md
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README.md
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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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- null
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metrics:
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- rouge
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model-index:
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- name: mt5-small-finetuned-amazon-en-es
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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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metrics:
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- name: Rouge1
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type: rouge
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value: 12.4927
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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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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.
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- Rouge1:
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- Rouge2:
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- Rougel:
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- Rougelsum:
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- Gen Len:
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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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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### Training results
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| Training Loss | Epoch | Step
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### Framework versions
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- Transformers 4.
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- Pytorch 1.9.1+cu111
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- Datasets 1.12.
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- Tokenizers 0.10.3
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tags:
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- summarization
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- generated_from_trainer
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metrics:
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- rouge
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model-index:
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- name: mt5-small-finetuned-amazon-en-es
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results: []
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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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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.5050
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- Rouge1: 16.471
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- Rouge2: 9.6857
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- Rougel: 16.1028
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- Rougelsum: 16.1929
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- Gen Len: 7.4538
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 8e-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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### 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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| 5.9093 | 1.0 | 1209 | 2.8536 | 9.0682 | 7.3025 | 8.7377 | 8.88 | 3.5504 |
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| 3.2481 | 2.0 | 2418 | 2.6507 | 16.3535 | 11.0792 | 16.0699 | 16.135 | 7.1387 |
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| 2.9617 | 3.0 | 3627 | 2.5843 | 15.2778 | 9.4619 | 15.0177 | 15.0804 | 7.4118 |
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| 2.8128 | 4.0 | 4836 | 2.5501 | 15.9292 | 9.3908 | 15.6132 | 15.6424 | 7.9286 |
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| 2.7324 | 5.0 | 6045 | 2.5321 | 16.1222 | 9.0046 | 15.7392 | 15.813 | 8.1471 |
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| 2.6572 | 6.0 | 7254 | 2.5073 | 17.4735 | 10.8534 | 17.0458 | 17.0905 | 6.9538 |
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| 2.6118 | 7.0 | 8463 | 2.5132 | 16.6198 | 9.8078 | 16.2883 | 16.3328 | 7.2605 |
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| 2.5818 | 8.0 | 9672 | 2.5050 | 16.471 | 9.6857 | 16.1028 | 16.1929 | 7.4538 |
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### Framework versions
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- Transformers 4.12.0.dev0
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- Pytorch 1.9.1+cu111
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- Datasets 1.12.2.dev0
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- Tokenizers 0.10.3
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