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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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model-index: |
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- name: roberta_gpt2_summarization_cnn_dailymail |
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results: [] |
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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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# roberta_gpt2_summarization_cnn_dailymail |
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This model is a fine-tuned version of [](https://huggingface.co/) on the cnn_dailymail dataset. |
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## Model description |
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This model uses RoBerta encoder and GPT2 decoder and fine-tuned on the summarization task. It got Rouge scores as follow: |
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Rouge1= 34.598 |
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Rouge2= 16.66 |
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RougeL= 26.259 |
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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: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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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- lr_scheduler_warmup_steps: 2000 |
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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 4.12.0.dev0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.16.1 |
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- Tokenizers 0.10.3 |
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