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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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metrics: |
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- rouge |
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model-index: |
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- name: t5-base-finetuned-multi-news |
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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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# t5-base-finetuned-multi-news |
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This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2612 |
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- Rouge1: 16.6322 |
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- Rouge2: 5.7556 |
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- Rougel: 12.4728 |
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- Rougelsum: 14.4814 |
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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: 4 |
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- eval_batch_size: 4 |
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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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| 2.5641 | 1.0 | 1250 | 2.2636 | 16.6762 | 5.7127 | 12.4648 | 14.5499 | |
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| 2.3542 | 2.0 | 2500 | 2.2439 | 16.7381 | 5.7345 | 12.5515 | 14.5785 | |
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| 2.2487 | 3.0 | 3750 | 2.2388 | 16.8879 | 5.8792 | 12.6417 | 14.8011 | |
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| 2.1705 | 4.0 | 5000 | 2.2413 | 16.5921 | 5.7804 | 12.4539 | 14.4865 | |
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| 2.1083 | 5.0 | 6250 | 2.2459 | 16.6878 | 5.8593 | 12.5132 | 14.5473 | |
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| 2.0622 | 6.0 | 7500 | 2.2495 | 16.7267 | 5.7825 | 12.48 | 14.5309 | |
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| 2.0297 | 7.0 | 8750 | 2.2581 | 16.633 | 5.748 | 12.4418 | 14.4796 | |
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| 2.0084 | 8.0 | 10000 | 2.2612 | 16.6322 | 5.7556 | 12.4728 | 14.4814 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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