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--- |
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license: apache-2.0 |
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base_model: google-t5/t5-small |
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tags: |
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- generated_from_trainer |
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datasets: |
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- lilferrit/xsum_t5_distillation |
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metrics: |
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- rouge |
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model-index: |
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- name: xsum_aligned_smallT5 |
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results: |
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- task: |
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name: Summarization |
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type: summarization |
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dataset: |
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name: lilferrit/xsum_t5_distillation |
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type: lilferrit/xsum_t5_distillation |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 28.6381 |
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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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# xsum_aligned_smallT5 |
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This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the lilferrit/xsum_t5_distillation dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.5258 |
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- Rouge1: 28.6381 |
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- Rouge2: 7.1512 |
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- Rougel: 21.3477 |
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- Rougelsum: 21.2928 |
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- Gen Len: 27.92 |
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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: 0.0002 |
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- train_batch_size: 8 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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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- training_steps: 200 |
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### Training results |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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