--- license: apache-2.0 tags: - generated_from_trainer datasets: - summarize_from_feedback metrics: - rouge model-index: - name: flan-t5-large-finetuned-openai-summarize_from_feedback results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: summarize_from_feedback type: summarize_from_feedback config: comparisons split: train args: comparisons metrics: - name: Rouge1 type: rouge value: 30.2401 - name: Rouge2 type: rouge value: 11.4916 - name: RougeL type: rouge value: 24.6485 - name: RougeLSum type: rouge value: 26.1801 pipeline_tag: summarization --- # flan-t5-large-finetuned-openai-summarize_from_feedback This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the summarize_from_feedback dataset. It achieves the following results on the evaluation set: - Loss: 2.3118 - Rouge1: 30.2401 - Rouge2: 11.4916 - Rougel: 24.6485 - Rougelsum: 26.1801 - Gen Len: 18.8428 ## 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: 5e-05 - train_batch_size: 16 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 6 ### Training results See [Tensorboard](https://huggingface.co/mrm8488/flan-t5-large-finetuned-openai-summarize_from_feedback/tensorboard) ### Citation ``` @misc {manuel_romero_2023, author = { {Manuel Romero} }, title = { flan-t5-large-finetuned-openai-summarize_from_feedback (Revision 51666f9) }, year = 2023, url = { https://huggingface.co/mrm8488/flan-t5-large-finetuned-openai-summarize_from_feedback }, doi = { 10.57967/hf/0266 }, publisher = { Hugging Face } } ``` ### Framework versions - Transformers 4.25.1 - Pytorch 1.13.0+cu116 - Datasets 2.8.0 - Tokenizers 0.13.2