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---
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
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