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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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- filter_sort |
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metrics: |
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- rouge |
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model-index: |
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- name: favsbot_filtersort_using_t5_summarization |
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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: filter_sort |
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type: filter_sort |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 15.7351 |
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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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# favsbot_filtersort_using_t5_summarization |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the filter_sort dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3327 |
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- Rouge1: 15.7351 |
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- Rouge2: 0.0 |
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- Rougel: 13.4803 |
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- Rougelsum: 13.5134 |
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- Gen Len: 12.6667 |
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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: 20 |
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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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| No log | 1.0 | 5 | 3.8161 | 14.754 | 0.0 | 12.6197 | 12.6426 | 10.5 | |
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| 4.8789 | 2.0 | 10 | 3.6423 | 14.754 | 0.0 | 12.6197 | 12.6426 | 10.5 | |
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| 4.8789 | 3.0 | 15 | 3.4687 | 14.754 | 0.0 | 12.6197 | 12.6426 | 10.5 | |
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| 4.5407 | 4.0 | 20 | 3.3086 | 14.754 | 0.0 | 12.6197 | 12.6426 | 10.5 | |
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| 4.5407 | 5.0 | 25 | 3.1726 | 14.754 | 0.0 | 12.6197 | 12.6426 | 10.5 | |
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| 4.2216 | 6.0 | 30 | 3.0464 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 | |
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| 4.2216 | 7.0 | 35 | 2.9326 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 | |
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| 4.0021 | 8.0 | 40 | 2.8305 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 | |
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| 4.0021 | 9.0 | 45 | 2.7386 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 | |
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| 3.7634 | 10.0 | 50 | 2.6588 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 | |
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| 3.7634 | 11.0 | 55 | 2.5916 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 | |
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| 3.6224 | 12.0 | 60 | 2.5358 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 | |
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| 3.6224 | 13.0 | 65 | 2.4895 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 | |
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| 3.496 | 14.0 | 70 | 2.4486 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 | |
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| 3.496 | 15.0 | 75 | 2.4140 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 | |
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| 3.4157 | 16.0 | 80 | 2.3857 | 15.7351 | 0.0 | 13.4803 | 13.5134 | 12.6667 | |
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| 3.4157 | 17.0 | 85 | 2.3622 | 15.7351 | 0.0 | 13.4803 | 13.5134 | 12.6667 | |
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| 3.3964 | 18.0 | 90 | 2.3455 | 15.7351 | 0.0 | 13.4803 | 13.5134 | 12.6667 | |
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| 3.3964 | 19.0 | 95 | 2.3361 | 15.7351 | 0.0 | 13.4803 | 13.5134 | 12.6667 | |
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| 3.3502 | 20.0 | 100 | 2.3327 | 15.7351 | 0.0 | 13.4803 | 13.5134 | 12.6667 | |
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### Framework versions |
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- Transformers 4.21.1 |
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- Pytorch 1.12.1 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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