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--- |
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license: apache-2.0 |
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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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metrics: |
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- rouge |
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model-index: |
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- name: flan-t5-base-cnn_dailymail |
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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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config: 3.0.0 |
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split: test |
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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: 24.6545 |
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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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# flan-t5-base-cnn_dailymail |
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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: 1.8013 |
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- Rouge1: 24.6545 |
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- Rouge2: 11.7282 |
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- Rougel: 20.3578 |
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- Rougelsum: 23.1966 |
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- Gen Len: 18.9989 |
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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: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
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| 2.0058 | 1.0 | 17945 | 1.8259 | 24.6279 | 11.6692 | 20.3361 | 23.1875 | 18.9988 | |
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| 1.97 | 2.0 | 35890 | 1.8158 | 24.6935 | 11.7554 | 20.4015 | 23.2584 | 18.9985 | |
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| 1.962 | 3.0 | 53835 | 1.8095 | 24.6151 | 11.7178 | 20.3361 | 23.1781 | 18.9993 | |
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| 1.9551 | 4.0 | 71780 | 1.8040 | 24.6127 | 11.7364 | 20.3473 | 23.17 | 18.9989 | |
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| 1.9515 | 5.0 | 89725 | 1.8013 | 24.6545 | 11.7282 | 20.3578 | 23.1966 | 18.9989 | |
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### Framework versions |
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- Transformers 4.29.1 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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