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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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widget: |
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- text: "As the demands of climate change grow, businesses are realizing the imperative of embracing sustainability. |
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Driven by ecological necessity and evolving consumer expectations, this shift necessitates a complete overhaul |
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of traditional business models towards a circular economy, emphasizing resource efficiency and waste reduction.\n |
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Adopting sustainable practices offers businesses multiple benefits: reduced operating costs, enhanced brand reputation, and increased customer loyalty. |
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As such, sustainability is a strategic tool for businesses looking to future-proof themselves.\n" |
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model-index: |
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- name: t5-base-news_headlines |
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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-news_headlines |
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This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an valurank/News_headlines dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9975 |
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- Rouge1: 53.7064 |
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- Rouge2: 34.6278 |
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- Rougel: 50.5129 |
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- Rougelsum: 50.5108 |
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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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- weight_decay: 0.01 |
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- lr_scheduler_type: linear |
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- num_epochs: 7 |
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- max_text_length: 512 |
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- max_target_length: 16 |
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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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| 1.9933 | 1.0 | 1531 | 1.4942 | 44.2439 | 22.1239 | 40.5281 | 40.5525 | |
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| 1.6029 | 2.0 | 3062 | 1.2824 | 46.5726 | 25.1122 | 43.131 | 43.151 | |
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| 1.409 | 3.0 | 4593 | 1.2358 | 48.3188 | 27.7403 | 44.9576 | 45.0009 | |
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| 1.2699 | 4.0 | 6124 | 1.1600 | 50.9858 | 30.6655 | 47.775 | 47.8414 | |
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| 1.1696 | 5.0 | 7655 | 1.0607 | 52.2212 | 32.6952 | 49.0023 | 49.0812 | |
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| 1.0934 | 6.0 | 9186 | 1.0173 | 53.1629 | 33.9552 | 49.9629 | 50.0118 | |
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| 1.049 | 7.0 | 10717 | 0.9975 | 53.7064 | 34.6278 | 50.5129 | 50.5108 | |
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### Framework versions |
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- Transformers 4.28.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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