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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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datasets: |
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- pubmed-summarization |
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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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dataset: |
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name: pubmed-summarization |
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type: pubmed-summarization |
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config: section |
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split: validation |
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args: section |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 14.1074 |
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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 pubmed-summarization dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3381 |
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- Rouge1: 14.1074 |
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- Rouge2: 5.3407 |
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- Rougel: 11.9593 |
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- Rougelsum: 12.9286 |
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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: 6 |
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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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| 3.0498 | 1.0 | 2500 | 2.4883 | 12.7167 | 5.1639 | 10.969 | 11.902 | |
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| 2.8737 | 2.0 | 5000 | 2.4022 | 13.812 | 5.1042 | 11.7056 | 12.6907 | |
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| 2.7603 | 3.0 | 7500 | 2.3895 | 13.6588 | 5.1146 | 11.6214 | 12.5331 | |
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| 2.6946 | 4.0 | 10000 | 2.3523 | 13.7167 | 5.2024 | 11.669 | 12.5419 | |
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| 2.6527 | 5.0 | 12500 | 2.3383 | 14.082 | 5.2787 | 11.9031 | 12.875 | |
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| 2.6303 | 6.0 | 15000 | 2.3381 | 14.1074 | 5.3407 | 11.9593 | 12.9286 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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