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--- |
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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-XSum-base |
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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: train |
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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: 0.273 |
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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-XSum-base |
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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: 2.5491 |
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- Rouge1: 0.273 |
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- Rouge2: 0.0711 |
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- Rougel: 0.2134 |
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- Rougelsum: 0.2134 |
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- Gen Len: 18.8194 |
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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: 3 |
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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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| 2.8234 | 1.0 | 2041 | 2.5916 | 0.2623 | 0.0647 | 0.2043 | 0.2044 | 18.8152 | |
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| 2.7742 | 2.0 | 4082 | 2.5577 | 0.2707 | 0.0702 | 0.2118 | 0.2117 | 18.8212 | |
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| 2.7482 | 3.0 | 6123 | 2.5491 | 0.273 | 0.0711 | 0.2134 | 0.2134 | 18.8194 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 1.12.0+cu116 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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