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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-samsum5 |
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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: 46.8382 |
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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-samsum5 |
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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: 1.3676 |
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- Rouge1: 46.8382 |
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- Rouge2: 23.107 |
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- Rougel: 39.5293 |
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- Rougelsum: 42.8917 |
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- Gen Len: 17.3675 |
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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: 6 |
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- eval_batch_size: 6 |
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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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| 1.4315 | 1.0 | 2456 | 1.3793 | 46.7908 | 22.8618 | 39.3679 | 43.0337 | 17.1148 | |
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| 1.352 | 2.0 | 4912 | 1.3676 | 46.8382 | 23.107 | 39.5293 | 42.8917 | 17.3675 | |
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| 1.2638 | 3.0 | 7368 | 1.3684 | 47.3491 | 23.5078 | 39.9401 | 43.4065 | 17.1832 | |
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| 1.2238 | 4.0 | 9824 | 1.3727 | 47.2949 | 23.8671 | 40.057 | 43.645 | 17.3260 | |
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| 1.1632 | 5.0 | 12280 | 1.3737 | 47.3124 | 23.7118 | 40.0067 | 43.6227 | 17.3126 | |
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### Framework versions |
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- Transformers 4.27.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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