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--- |
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license: apache-2.0 |
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base_model: google/flan-t5-small |
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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-small-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: 43.1157 |
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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-small-samsum |
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This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the samsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6670 |
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- Rouge1: 43.1157 |
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- Rouge2: 18.7389 |
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- Rougel: 35.4615 |
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- Rougelsum: 39.2648 |
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- Gen Len: 16.9109 |
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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: 32 |
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- eval_batch_size: 32 |
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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: 2 |
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- mixed_precision_training: Native AMP |
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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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| 1.8863 | 0.22 | 100 | 1.7049 | 42.1055 | 18.0331 | 34.7517 | 38.3767 | 16.5788 | |
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| 1.8463 | 0.43 | 200 | 1.6947 | 42.4427 | 18.2735 | 34.9451 | 38.8469 | 17.3614 | |
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| 1.8548 | 0.65 | 300 | 1.6792 | 42.6324 | 18.5506 | 35.1724 | 38.8717 | 17.1514 | |
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| 1.8358 | 0.87 | 400 | 1.6772 | 42.2127 | 18.2031 | 34.8749 | 38.3969 | 16.5873 | |
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| 1.8129 | 1.08 | 500 | 1.6729 | 42.6431 | 18.6961 | 35.4006 | 38.8667 | 16.9170 | |
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| 1.8068 | 1.3 | 600 | 1.6709 | 42.5591 | 18.3093 | 35.1272 | 38.6379 | 16.9451 | |
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| 1.7973 | 1.52 | 700 | 1.6687 | 42.8925 | 18.6265 | 35.292 | 38.9546 | 16.7546 | |
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| 1.7979 | 1.74 | 800 | 1.6668 | 42.9455 | 18.7294 | 35.4018 | 39.099 | 16.8791 | |
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| 1.7899 | 1.95 | 900 | 1.6670 | 43.1157 | 18.7389 | 35.4615 | 39.2648 | 16.9109 | |
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### Framework versions |
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- Transformers 4.36.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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