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--- |
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license: apache-2.0 |
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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-base-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: 47.4485 |
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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-base-samsum |
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This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the samsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3772 |
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- Rouge1: 47.4485 |
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- Rouge2: 23.938 |
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- Rougel: 40.0491 |
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- Rougelsum: 43.6954 |
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- Gen Len: 17.3162 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 5 |
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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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| 1.4264 | 1.0 | 1842 | 1.3829 | 46.5615 | 23.1026 | 39.4012 | 42.9128 | 17.0977 | |
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| 1.3527 | 2.0 | 3684 | 1.3732 | 47.1096 | 23.4582 | 39.5488 | 43.2577 | 17.4554 | |
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| 1.2554 | 3.0 | 5526 | 1.3709 | 46.9079 | 23.29 | 39.5731 | 43.1779 | 17.2027 | |
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| 1.2503 | 4.0 | 7368 | 1.3736 | 47.4506 | 23.7238 | 39.9803 | 43.5976 | 17.2198 | |
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| 1.1675 | 5.0 | 9210 | 1.3772 | 47.4485 | 23.938 | 40.0491 | 43.6954 | 17.3162 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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