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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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- amazon_reviews_multi
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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-kitchen-reviews
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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: amazon_reviews_multi
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type: amazon_reviews_multi
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config: en
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split: train
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args: en
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metrics:
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- name: Rouge1
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type: rouge
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value: 19.1669
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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-small-finetuned-amazon-en-kitchen-reviews
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the amazon_reviews_multi dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0960
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- Rouge1: 19.1669
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- Rouge2: 10.8937
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- Rougel: 18.6296
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- Rougelsum: 18.7486
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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: 8
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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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| 13.803 | 1.0 | 827 | 2.4239 | 1.7983 | 0.0 | 1.8317 | 1.7854 |
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| 1.938 | 2.0 | 1654 | 1.2836 | 14.9804 | 4.7997 | 14.3848 | 14.4255 |
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| 1.2922 | 3.0 | 2481 | 1.1718 | 16.3574 | 7.2689 | 15.6126 | 15.5685 |
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| 1.1463 | 4.0 | 3308 | 1.1265 | 17.6554 | 8.9813 | 17.1575 | 17.2073 |
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| 1.078 | 5.0 | 4135 | 1.1085 | 19.2978 | 11.5604 | 18.8279 | 18.9399 |
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| 1.0453 | 6.0 | 4962 | 1.1070 | 19.3828 | 11.0161 | 18.7636 | 18.9002 |
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| 1.0233 | 7.0 | 5789 | 1.1004 | 19.0604 | 10.5071 | 18.341 | 18.4669 |
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| 1.012 | 8.0 | 6616 | 1.0960 | 19.1669 | 10.8937 | 18.6296 | 18.7486 |
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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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