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--- |
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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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language: |
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- en |
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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-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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args: default |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 27.7165 |
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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-finetuned-xsum |
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This model is a fine-tuned version of [st3rl4nce/t5-small-finetuned-xsum](https://huggingface.co/st3rl4nce/t5-small-finetuned-xsum) on the xsum dataset. |
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It achieves the following results on the evaluation set: |
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- eval_loss: 2.5146 |
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- eval_rouge1: 27.7165 |
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- eval_rouge2: 7.3585 |
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- eval_rougeL: 21.7684 |
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- eval_rougeLsum: 21.7758 |
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- eval_gen_len: 18.8131 |
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- eval_runtime: 667.5713 |
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- eval_samples_per_second: 16.975 |
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- eval_steps_per_second: 1.062 |
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- epoch: 0.01 |
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- step: 113 |
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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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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
