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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: 42.6222 |
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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: 1.6729 |
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- Rouge1: 42.6222 |
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- Rouge2: 18.682 |
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- Rougel: 35.3954 |
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- Rougelsum: 38.9104 |
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- Gen Len: 16.9170 |
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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 | 42.1145 | 18.0254 | 34.733 | 38.4052 | 16.5788 | |
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| 1.8463 | 0.43 | 200 | 1.6947 | 42.4119 | 18.2925 | 34.9702 | 38.8535 | 17.3614 | |
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| 1.8548 | 0.65 | 300 | 1.6792 | 42.5967 | 18.5244 | 35.1965 | 38.9087 | 17.1514 | |
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| 1.8358 | 0.87 | 400 | 1.6772 | 42.167 | 18.2032 | 34.8647 | 38.4144 | 16.5873 | |
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| 1.8129 | 1.08 | 500 | 1.6729 | 42.6222 | 18.682 | 35.3954 | 38.9104 | 16.9170 | |
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| 1.8068 | 1.3 | 600 | 1.6709 | 42.5238 | 18.311 | 35.1257 | 38.6584 | 16.9451 | |
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| 1.7973 | 1.52 | 700 | 1.6687 | 42.8715 | 18.6133 | 35.3054 | 38.971 | 16.7546 | |
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| 1.7979 | 1.74 | 800 | 1.6668 | 42.9038 | 18.7483 | 35.4156 | 39.1118 | 16.8791 | |
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| 1.7899 | 1.95 | 900 | 1.6670 | 43.1142 | 18.7369 | 35.4796 | 39.2724 | 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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