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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: large |
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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: 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: 39.7125 |
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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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# large |
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This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the xsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: nan |
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- Rouge1: 39.7125 |
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- Rouge2: 16.3418 |
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- Rougel: 31.7246 |
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- Rougelsum: 31.7214 |
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- Gen Len: 26.7397 |
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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: 0.0001 |
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- train_batch_size: 8 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant |
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- num_epochs: 3.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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### Framework versions |
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- Transformers 4.27.0.dev0 |
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- Pytorch 1.9.0+cu111 |
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- Datasets 2.5.1 |
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- Tokenizers 0.12.1 |
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