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README.md
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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_b4_lr3e-5
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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: 26.1071
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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_b4_lr3e-5
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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: 2.4351
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- Rouge1: 26.1071
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- Rouge2: 9.3627
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- Rougel: 22.0825
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- Rougelsum: 25.4514
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- Gen Len: 18.474
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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: 3e-05
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- train_batch_size: 4
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- eval_batch_size: 4
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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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| 2.9216 | 0.13 | 5000 | 2.6385 | 23.8039 | 7.8863 | 20.0109 | 23.0802 | 18.3481 |
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| 2.8158 | 0.25 | 10000 | 2.5884 | 24.2567 | 8.2003 | 20.438 | 23.5325 | 18.3833 |
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| 2.7743 | 0.38 | 15000 | 2.5623 | 24.8471 | 8.3768 | 20.8711 | 24.1114 | 18.2901 |
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| 2.7598 | 0.51 | 20000 | 2.5368 | 25.1566 | 8.6721 | 21.1896 | 24.4558 | 18.3561 |
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| 2.7192 | 0.64 | 25000 | 2.5220 | 25.3477 | 8.8106 | 21.3799 | 24.6742 | 18.3108 |
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| 2.7207 | 0.76 | 30000 | 2.5114 | 25.5912 | 8.998 | 21.5508 | 24.9344 | 18.3445 |
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| 2.7041 | 0.89 | 35000 | 2.4993 | 25.457 | 8.8644 | 21.4516 | 24.7965 | 18.4354 |
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| 2.687 | 1.02 | 40000 | 2.4879 | 25.5886 | 8.9766 | 21.6794 | 24.9512 | 18.4035 |
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| 2.6652 | 1.14 | 45000 | 2.4848 | 25.7367 | 9.078 | 21.7096 | 25.0924 | 18.4328 |
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| 2.6536 | 1.27 | 50000 | 2.4761 | 25.7368 | 9.1609 | 21.729 | 25.0866 | 18.3117 |
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| 2.6589 | 1.4 | 55000 | 2.4702 | 25.7738 | 9.1413 | 21.7492 | 25.114 | 18.4862 |
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| 2.6384 | 1.53 | 60000 | 2.4620 | 25.7433 | 9.1356 | 21.8198 | 25.0896 | 18.489 |
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| 2.6337 | 1.65 | 65000 | 2.4595 | 26.0919 | 9.2605 | 21.9447 | 25.4065 | 18.4083 |
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| 2.6375 | 1.78 | 70000 | 2.4557 | 26.0912 | 9.3469 | 22.0182 | 25.4428 | 18.4133 |
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| 2.6441 | 1.91 | 75000 | 2.4502 | 26.1366 | 9.3143 | 22.058 | 25.4673 | 18.4972 |
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| 2.6276 | 2.03 | 80000 | 2.4478 | 25.9929 | 9.2464 | 21.9271 | 25.3263 | 18.469 |
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| 2.6062 | 2.16 | 85000 | 2.4467 | 26.0465 | 9.3166 | 22.0342 | 25.3998 | 18.3777 |
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| 2.6126 | 2.29 | 90000 | 2.4407 | 26.1953 | 9.3848 | 22.1148 | 25.5161 | 18.467 |
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| 2.6182 | 2.42 | 95000 | 2.4397 | 26.1331 | 9.3626 | 22.1076 | 25.4627 | 18.4413 |
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| 2.6041 | 2.54 | 100000 | 2.4375 | 26.1301 | 9.3567 | 22.0869 | 25.465 | 18.4929 |
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| 2.5996 | 2.67 | 105000 | 2.4367 | 26.0956 | 9.3314 | 22.063 | 25.4242 | 18.5074 |
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| 2.6144 | 2.8 | 110000 | 2.4355 | 26.1764 | 9.4157 | 22.1231 | 25.5175 | 18.4729 |
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| 2.608 | 2.93 | 115000 | 2.4351 | 26.1071 | 9.3627 | 22.0825 | 25.4514 | 18.474 |
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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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