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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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- summarization |
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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: 10.8752 |
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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-es |
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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: 3.1491 |
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- Rouge1: 10.8752 |
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- Rouge2: 3.8695 |
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- Rougel: 10.6991 |
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- Rougelsum: 10.6616 |
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- Gen Len: 5.6085 |
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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: 2e-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: 6 |
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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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| 9.1733 | 1.0 | 2202 | 3.4863 | 6.3629 | 1.4637 | 6.2501 | 6.2752 | 3.3302 | |
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| 4.4547 | 2.0 | 4404 | 3.2809 | 9.1283 | 2.992 | 8.9851 | 9.0487 | 4.7642 | |
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| 4.0581 | 3.0 | 6606 | 3.2108 | 10.5207 | 3.7411 | 10.2595 | 10.234 | 5.3208 | |
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| 3.8821 | 4.0 | 8808 | 3.1701 | 10.8636 | 4.0944 | 10.6462 | 10.6468 | 5.2453 | |
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| 3.7857 | 5.0 | 11010 | 3.1600 | 10.9456 | 4.5187 | 10.784 | 10.7542 | 5.691 | |
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| 3.7273 | 6.0 | 13212 | 3.1491 | 10.8752 | 3.8695 | 10.6991 | 10.6616 | 5.6085 | |
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### Framework versions |
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- Transformers 4.10.3 |
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- Pytorch 1.9.1+cu102 |
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- Datasets 1.12.1 |
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- Tokenizers 0.10.3 |
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