| --- |
| 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 I need review document before leaves our company need know when leave" |
| example_title: "review document" |
| - 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: "dear william I out yesterday received message today will get back today" |
| example_title: "message" |
| - 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" |
| 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: 2.5 |
| length_penalty: 0.9 |
| --- |
| |
|
|
| # t5-small-kw2email-v2 |
|
|
| This model is a fine-tuned version of [postbot/t5-small-kw2email](https://huggingface.co/postbot/t5-small-kw2email) 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: 0.0001 |
| - train_batch_size: 16 |
| - eval_batch_size: 2 |
| - seed: 42 |
| - distributed_type: multi-GPU |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 64 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_ratio: 0.01 |
| - num_epochs: 4 |
| |
| ### Training results |
| |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.21.1 |
| - Pytorch 1.12.0+cu113 |
| - Datasets 2.4.0 |
| - Tokenizers 0.12.1 |
| |
