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--- |
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license: apache-2.0 |
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tags: |
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- summarization |
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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: t5-small-finetuned-cnn-v2 |
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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: cnn_dailymail |
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type: cnn_dailymail |
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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: 35.154 |
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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-cnn-v2 |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the cnn_dailymail dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5474 |
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- Rouge1: 35.154 |
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- Rouge2: 18.683 |
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- Rougel: 30.8481 |
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- Rougelsum: 32.9638 |
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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: 5.6e-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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- num_epochs: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
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| 1.8823 | 1.0 | 35890 | 1.5878 | 34.9676 | 18.4927 | 30.6753 | 32.7702 | |
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| 1.7871 | 2.0 | 71780 | 1.5709 | 34.9205 | 18.5556 | 30.6514 | 32.745 | |
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| 1.7507 | 3.0 | 107670 | 1.5586 | 34.9825 | 18.4964 | 30.6724 | 32.7644 | |
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| 1.7253 | 4.0 | 143560 | 1.5584 | 35.074 | 18.6171 | 30.8007 | 32.9132 | |
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| 1.705 | 5.0 | 179450 | 1.5528 | 35.023 | 18.5787 | 30.7014 | 32.8396 | |
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| 1.6894 | 6.0 | 215340 | 1.5518 | 35.0583 | 18.6754 | 30.791 | 32.8814 | |
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| 1.6776 | 7.0 | 251230 | 1.5468 | 35.2236 | 18.6812 | 30.8944 | 33.0362 | |
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| 1.6687 | 8.0 | 287120 | 1.5474 | 35.154 | 18.683 | 30.8481 | 32.9638 | |
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### Framework versions |
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- Transformers 4.14.0 |
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- Pytorch 1.5.0 |
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- Datasets 2.3.2 |
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- Tokenizers 0.10.3 |
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