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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: 42.6557 |
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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: 1.6754 |
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- Rouge1: 42.6557 |
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- Rouge2: 18.3585 |
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- Rougel: 35.2496 |
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- Rougelsum: 38.866 |
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- Gen Len: 16.8474 |
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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: 52 |
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- eval_batch_size: 52 |
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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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| 1.8824 | 0.35 | 100 | 1.7015 | 42.4532 | 18.3147 | 35.0815 | 38.7699 | 16.6532 | |
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| 1.8578 | 0.7 | 200 | 1.6878 | 41.9748 | 18.2334 | 34.934 | 38.4167 | 16.7216 | |
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| 1.835 | 1.06 | 300 | 1.6823 | 42.7247 | 18.6058 | 35.402 | 38.9437 | 16.9048 | |
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| 1.8144 | 1.41 | 400 | 1.6786 | 42.5857 | 18.3954 | 35.3072 | 38.8397 | 16.6618 | |
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| 1.8094 | 1.76 | 500 | 1.6754 | 42.6557 | 18.3585 | 35.2496 | 38.866 | 16.8474 | |
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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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