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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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- samsum |
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metrics: |
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- rouge |
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model-index: |
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- name: t5-small-finetuned-samsum-en |
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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: samsum |
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type: samsum |
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args: samsum |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 44.3313 |
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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-samsum-en |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the samsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9335 |
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- Rouge1: 44.3313 |
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- Rouge2: 20.71 |
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- Rougel: 37.221 |
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- Rougelsum: 40.9603 |
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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: 10 |
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- eval_batch_size: 10 |
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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: 10 |
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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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| 1.4912 | 1.0 | 300 | 1.9043 | 44.1517 | 20.0186 | 36.6053 | 40.5164 | |
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| 1.5055 | 2.0 | 600 | 1.8912 | 44.1473 | 20.4456 | 37.069 | 40.6714 | |
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| 1.4852 | 3.0 | 900 | 1.8986 | 44.7536 | 20.8646 | 37.525 | 41.2189 | |
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| 1.4539 | 4.0 | 1200 | 1.9136 | 44.2144 | 20.3446 | 37.1088 | 40.7581 | |
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| 1.4262 | 5.0 | 1500 | 1.9215 | 44.2656 | 20.6044 | 37.3267 | 40.9469 | |
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| 1.4118 | 6.0 | 1800 | 1.9247 | 43.8793 | 20.4663 | 37.0614 | 40.6065 | |
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| 1.3987 | 7.0 | 2100 | 1.9256 | 43.9981 | 20.2703 | 36.7856 | 40.6354 | |
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| 1.3822 | 8.0 | 2400 | 1.9316 | 43.9732 | 20.4559 | 36.8039 | 40.5784 | |
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| 1.3773 | 9.0 | 2700 | 1.9314 | 44.3075 | 20.5435 | 37.0457 | 40.832 | |
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| 1.3795 | 10.0 | 3000 | 1.9335 | 44.3313 | 20.71 | 37.221 | 40.9603 | |
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### Framework versions |
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- Transformers 4.19.2 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.2.2 |
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- Tokenizers 0.12.1 |
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