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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: 42.6378 |
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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: 1.6629 |
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- Rouge1: 42.6378 |
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- Rouge2: 18.2896 |
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- Rougel: 35.1851 |
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- Rougelsum: 38.8113 |
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- Gen Len: 16.8596 |
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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: 40 |
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- eval_batch_size: 40 |
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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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| 1.7932 | 0.27 | 100 | 1.6830 | 42.7032 | 18.4803 | 35.278 | 38.9331 | 17.0403 | |
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| 1.8102 | 0.54 | 200 | 1.6701 | 42.2811 | 18.2246 | 35.0893 | 38.4619 | 16.7265 | |
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| 1.8279 | 0.81 | 300 | 1.6658 | 42.6465 | 18.6939 | 35.4208 | 38.9399 | 16.8120 | |
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| 1.802 | 1.08 | 400 | 1.6633 | 42.5867 | 18.3579 | 35.3253 | 38.7049 | 16.6862 | |
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| 1.773 | 1.36 | 500 | 1.6629 | 42.6378 | 18.2896 | 35.1851 | 38.8113 | 16.8596 | |
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| 1.7752 | 1.63 | 600 | 1.6598 | 42.7111 | 18.3689 | 35.4218 | 38.8698 | 16.9328 | |
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| 1.7688 | 1.9 | 700 | 1.6589 | 42.6972 | 18.3536 | 35.3153 | 38.7976 | 17.0073 | |
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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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