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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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- wikihow |
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metrics: |
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- rouge |
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model-index: |
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- name: t5-small-finetuned-wikihow_3epoch_b8_lr3e-3 |
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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: wikihow |
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type: wikihow |
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args: all |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 27.1711 |
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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-wikihow_3epoch_b8_lr3e-3 |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the wikihow dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3163 |
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- Rouge1: 27.1711 |
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- Rouge2: 10.6296 |
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- Rougel: 23.206 |
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- Rougelsum: 26.4801 |
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- Gen Len: 18.5433 |
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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: 0.003 |
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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: 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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| 3.0734 | 0.25 | 5000 | 2.7884 | 22.4825 | 7.2492 | 19.243 | 21.9167 | 18.0616 | |
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| 2.9201 | 0.51 | 10000 | 2.7089 | 24.0869 | 8.0348 | 20.4814 | 23.4541 | 18.5994 | |
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| 2.8403 | 0.76 | 15000 | 2.6390 | 24.62 | 8.3776 | 20.8736 | 23.9784 | 18.4676 | |
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| 2.7764 | 1.02 | 20000 | 2.5943 | 24.1504 | 8.3933 | 20.8271 | 23.5382 | 18.4078 | |
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| 2.6641 | 1.27 | 25000 | 2.5428 | 25.6574 | 9.2371 | 21.8576 | 24.9558 | 18.4249 | |
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| 2.6369 | 1.53 | 30000 | 2.5042 | 25.5208 | 9.254 | 21.6673 | 24.8589 | 18.6467 | |
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| 2.6 | 1.78 | 35000 | 2.4637 | 26.094 | 9.7003 | 22.3097 | 25.4695 | 18.5065 | |
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| 2.5562 | 2.03 | 40000 | 2.4285 | 26.5374 | 9.9222 | 22.5291 | 25.8836 | 18.5553 | |
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| 2.4322 | 2.29 | 45000 | 2.3858 | 26.939 | 10.3555 | 23.0211 | 26.2834 | 18.5614 | |
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| 2.4106 | 2.54 | 50000 | 2.3537 | 26.7423 | 10.2816 | 22.7986 | 26.083 | 18.5792 | |
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| 2.3731 | 2.8 | 55000 | 2.3163 | 27.1711 | 10.6296 | 23.206 | 26.4801 | 18.5433 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 2.0.0 |
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- Tokenizers 0.11.6 |
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