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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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- cnn_dailymail |
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metrics: |
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- rouge |
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model-index: |
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- name: large-5-6 |
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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: cnn_dailymail 3.0.0 |
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type: cnn_dailymail |
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config: 3.0.0 |
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split: validation |
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args: 3.0.0 |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 44.1017 |
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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-5-6 |
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This model is a fine-tuned version of [cnn/large-5-6/](https://huggingface.co/cnn/large-5-6/) on the cnn_dailymail 3.0.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2606 |
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- Rouge1: 44.1017 |
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- Rouge2: 21.128 |
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- Rougel: 31.584 |
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- Rougelsum: 41.2784 |
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- Gen Len: 71.0438 |
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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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### Training results |
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### Framework versions |
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- Transformers 4.27.0.dev0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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