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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: test |
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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: 47.5929 |
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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: 1.3776 |
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- Rouge1: 47.5929 |
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- Rouge2: 23.8272 |
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- Rougel: 40.1493 |
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- Rougelsum: 43.7798 |
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- Gen Len: 17.2503 |
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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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| 1.4416 | 1.0 | 1842 | 1.3837 | 46.6013 | 23.125 | 39.4894 | 42.9943 | 17.0684 | |
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| 1.3581 | 2.0 | 3684 | 1.3730 | 47.3142 | 23.5981 | 39.5786 | 43.447 | 17.3675 | |
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| 1.2781 | 3.0 | 5526 | 1.3739 | 47.5321 | 23.8035 | 40.0555 | 43.7595 | 17.2271 | |
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| 1.2368 | 4.0 | 7368 | 1.3767 | 47.0944 | 23.2414 | 39.6673 | 43.2155 | 17.2405 | |
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| 1.1953 | 5.0 | 9210 | 1.3776 | 47.5929 | 23.8272 | 40.1493 | 43.7798 | 17.2503 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.12.1 |
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- Datasets 2.9.0 |
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- Tokenizers 0.13.2 |
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