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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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- samsum |
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metrics: |
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- rouge |
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model-index: |
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- name: flan-t5-base-samsum |
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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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config: samsum |
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split: train |
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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: 47.2358 |
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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-samsum |
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This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the samsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3716 |
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- Rouge1: 47.2358 |
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- Rouge2: 23.5135 |
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- Rougel: 39.6266 |
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- Rougelsum: 43.3458 |
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- Gen Len: 17.3907 |
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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: 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: 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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| 1.4379 | 1.0 | 1842 | 1.3805 | 47.1075 | 23.531 | 39.6919 | 43.549 | 17.1197 | |
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| 1.3559 | 2.0 | 3684 | 1.3716 | 47.2358 | 23.5135 | 39.6266 | 43.3458 | 17.3907 | |
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| 1.2783 | 3.0 | 5526 | 1.3721 | 47.4581 | 23.7339 | 39.7726 | 43.4568 | 17.1832 | |
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| 1.2378 | 4.0 | 7368 | 1.3757 | 47.8557 | 24.0593 | 40.2324 | 44.0085 | 17.3053 | |
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| 1.1983 | 5.0 | 9210 | 1.3751 | 47.8156 | 24.0038 | 40.2169 | 43.8918 | 17.3040 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.8.0 |
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- Tokenizers 0.12.1 |
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