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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: 42.4655 |
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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: 1.6732 |
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- Rouge1: 42.4655 |
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- Rouge2: 18.4875 |
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- Rougel: 35.2198 |
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- Rougelsum: 38.6465 |
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- Gen Len: 16.8486 |
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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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| 1.8853 | 0.22 | 100 | 1.7046 | 42.3969 | 18.365 | 35.0091 | 38.6527 | 16.6703 | |
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| 1.8463 | 0.43 | 200 | 1.6954 | 42.5607 | 18.4425 | 35.1088 | 38.8749 | 17.3565 | |
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| 1.8549 | 0.65 | 300 | 1.6794 | 42.5148 | 18.4716 | 35.1769 | 38.7018 | 17.1123 | |
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| 1.8361 | 0.87 | 400 | 1.6775 | 42.3899 | 18.4343 | 35.134 | 38.5732 | 16.6215 | |
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| 1.8132 | 1.08 | 500 | 1.6732 | 42.4655 | 18.4875 | 35.2198 | 38.6465 | 16.8486 | |
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| 1.8073 | 1.3 | 600 | 1.6708 | 42.4741 | 18.3824 | 35.1819 | 38.6066 | 16.9475 | |
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| 1.7973 | 1.52 | 700 | 1.6686 | 42.8206 | 18.7011 | 35.3874 | 38.9173 | 16.7595 | |
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| 1.798 | 1.74 | 800 | 1.6666 | 42.7779 | 18.6627 | 35.323 | 38.9467 | 16.9389 | |
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| 1.79 | 1.95 | 900 | 1.6668 | 42.8071 | 18.7113 | 35.2872 | 38.8641 | 16.9426 | |
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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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