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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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- eli5 |
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metrics: |
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- rouge |
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model-index: |
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- name: t5-small-finetuned-eli5 |
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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: eli5 |
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type: eli5 |
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config: LFQA_reddit |
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split: train_eli5 |
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args: LFQA_reddit |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 9.944 |
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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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# t5-small-finetuned-eli5 |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the eli5 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.7275 |
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- Rouge1: 9.944 |
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- Rouge2: 1.908 |
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- Rougel: 8.0145 |
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- Rougelsum: 9.2275 |
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- Gen Len: 18.9988 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 3 |
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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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| 3.9806 | 1.0 | 17040 | 3.7726 | 9.8475 | 1.872 | 7.9462 | 9.1258 | 18.9972 | |
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| 3.9458 | 2.0 | 34080 | 3.7369 | 9.9232 | 1.8981 | 7.9922 | 9.2061 | 18.9988 | |
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| 3.9355 | 3.0 | 51120 | 3.7275 | 9.944 | 1.908 | 8.0145 | 9.2275 | 18.9988 | |
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### Framework versions |
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- Transformers 4.22.2 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.5.1 |
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- Tokenizers 0.12.1 |
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