--- license: apache-2.0 tags: - generated_from_trainer - email generation - email datasets: - aeslc - postbot/multi_emails_kw widget: - text: Thursday pay invoice need asap thanks Pierre good morning dear Harold example_title: invoice - text: dear elia when will space be ready need urgently regards ronald example_title: space ready - text: Tuesday need talk with you important stuff dear jonathan status war in Syria example_title: war status - text: dear bob will back wednesday need urgently regards elena example_title: return wednesday - text: dear mary thanks for your last invoice need know when payment be example_title: last invoice - text: pct1_dropremainder rounding may truncate the last examples in a dataset if the number of examples in your dataset don’t divide evenly by 100 dear bob example_title: pct1_dropremainder - text: dear joseph have all invoices ready Monday next invoice in 30 days have great weekend example_title: next invoice - text: dear mary I have couple questions on new contract we agreed on need know thoughts regarding contract example_title: contract - text: Friday will make report due soon please thanks dear john example_title: report due soon - text: need take photos sunday want finish thursday photo exhibition need urgent help thanks dear john example_title: photo exhibition - text: Tuesday need talk with you important stuff dear reginald example_title: important talk - text: dear maria how are you doing thanks very much example_title: thanks - text: dear james tomorrow will prepare file for june report before leave need know when leave example_title: file for june report parameters: min_length: 16 max_length: 256 no_repeat_ngram_size: 2 do_sample: false num_beams: 8 early_stopping: true repetition_penalty: 5.5 length_penalty: 0.9 base_model: pszemraj/t5-base-kw2email-v3.5 --- # t5-base-kw2email-v4 This version **improves on prior "base" versions** by using training hyperparameters more closely aligned with [bigscience/T0](https://huggingface.co/bigscience/T0) This model is a fine-tuned version of [pszemraj/t5-base-kw2email-v3.5](https://huggingface.co/pszemraj/t5-base-kw2email-v3.5) on the None dataset. ## 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: 0.001 - train_batch_size: 8 - eval_batch_size: 2 - seed: 42 - distributed_type: multi-GPU - gradient_accumulation_steps: 32 - total_train_batch_size: 256 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.03 - num_epochs: 2 ### Training results ### Framework versions - Transformers 4.21.2 - Pytorch 1.12.1+cu113 - Datasets 2.4.0 - Tokenizers 0.12.1