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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: t5-small |
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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 |
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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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config: default |
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split: validation |
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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: 26.2006 |
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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 |
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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: 2.6282 |
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- Rouge1: 26.2006 |
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- Rouge2: 6.4986 |
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- Rougel: 20.4525 |
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- Rougelsum: 20.4233 |
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- Gen Len: 18.791 |
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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: 5 |
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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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| 3.0796 | 1.0 | 500 | 2.6971 | 23.5102 | 5.0088 | 18.4369 | 18.4317 | 18.719 | |
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| 2.8953 | 2.0 | 1000 | 2.6563 | 25.1823 | 5.9526 | 19.6696 | 19.6505 | 18.779 | |
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| 2.8527 | 3.0 | 1500 | 2.6393 | 25.7775 | 6.2129 | 20.1822 | 20.1652 | 18.79 | |
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| 2.8301 | 4.0 | 2000 | 2.6307 | 25.899 | 6.2538 | 20.2373 | 20.222 | 18.802 | |
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| 2.8158 | 5.0 | 2500 | 2.6282 | 26.2006 | 6.4986 | 20.4525 | 20.4233 | 18.791 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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