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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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- xsum |
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metrics: |
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- rouge |
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model-index: |
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- name: t5-small-finetuned-xsum-512 |
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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: xsum |
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type: xsum |
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args: default |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 28.8448 |
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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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# t5-small-finetuned-xsum-512 |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.4706 |
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- Rouge1: 28.8448 |
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- Rouge2: 7.9819 |
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- Rougel: 22.8686 |
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- Rougelsum: 22.8754 |
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- Gen Len: 18.7654 |
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T5, zero-shot on the same evaluation set: |
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`{'rouge1': 19.2304, 'rouge2': 2.5842, 'rougeL': 13.9683, 'rougeLsum': 15.516}` |
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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: 16 |
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- eval_batch_size: 16 |
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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: 1 |
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- mixed_precision_training: Native AMP |
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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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| 2.7057 | 1.0 | 7854 | 2.4706 | 28.8448 | 7.9819 | 22.8686 | 22.8754 | 18.7654 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 1.10.2 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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