--- license: apache-2.0 tags: - generated_from_trainer datasets: - filter_sort metrics: - rouge model-index: - name: favsbot_filtersort_using_t5_summarization results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: filter_sort type: filter_sort config: default split: train args: default metrics: - name: Rouge1 type: rouge value: 15.7351 --- # favsbot_filtersort_using_t5_summarization This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the filter_sort dataset. It achieves the following results on the evaluation set: - Loss: 2.3327 - Rouge1: 15.7351 - Rouge2: 0.0 - Rougel: 13.4803 - Rougelsum: 13.5134 - Gen Len: 12.6667 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 20 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:| | No log | 1.0 | 5 | 3.8161 | 14.754 | 0.0 | 12.6197 | 12.6426 | 10.5 | | 4.8789 | 2.0 | 10 | 3.6423 | 14.754 | 0.0 | 12.6197 | 12.6426 | 10.5 | | 4.8789 | 3.0 | 15 | 3.4687 | 14.754 | 0.0 | 12.6197 | 12.6426 | 10.5 | | 4.5407 | 4.0 | 20 | 3.3086 | 14.754 | 0.0 | 12.6197 | 12.6426 | 10.5 | | 4.5407 | 5.0 | 25 | 3.1726 | 14.754 | 0.0 | 12.6197 | 12.6426 | 10.5 | | 4.2216 | 6.0 | 30 | 3.0464 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 | | 4.2216 | 7.0 | 35 | 2.9326 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 | | 4.0021 | 8.0 | 40 | 2.8305 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 | | 4.0021 | 9.0 | 45 | 2.7386 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 | | 3.7634 | 10.0 | 50 | 2.6588 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 | | 3.7634 | 11.0 | 55 | 2.5916 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 | | 3.6224 | 12.0 | 60 | 2.5358 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 | | 3.6224 | 13.0 | 65 | 2.4895 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 | | 3.496 | 14.0 | 70 | 2.4486 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 | | 3.496 | 15.0 | 75 | 2.4140 | 15.7792 | 0.0 | 13.5134 | 13.5411 | 12.6667 | | 3.4157 | 16.0 | 80 | 2.3857 | 15.7351 | 0.0 | 13.4803 | 13.5134 | 12.6667 | | 3.4157 | 17.0 | 85 | 2.3622 | 15.7351 | 0.0 | 13.4803 | 13.5134 | 12.6667 | | 3.3964 | 18.0 | 90 | 2.3455 | 15.7351 | 0.0 | 13.4803 | 13.5134 | 12.6667 | | 3.3964 | 19.0 | 95 | 2.3361 | 15.7351 | 0.0 | 13.4803 | 13.5134 | 12.6667 | | 3.3502 | 20.0 | 100 | 2.3327 | 15.7351 | 0.0 | 13.4803 | 13.5134 | 12.6667 | ### Framework versions - Transformers 4.21.1 - Pytorch 1.12.1 - Datasets 2.4.0 - Tokenizers 0.12.1