README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
  - distilgpt2
  - email generation
  - email
datasets:
  - aeslc
  - postbot/multi-emails-100k
widget:
  - text: >-
      Good Morning Professor Beans,

      Hope you are doing well. I just wanted to reach out and ask if
      differential calculus will be on the exam
    example_title: email to prof
  - text: >-
      Hey <NAME>,


      Thank you for signing up for my weekly newsletter. Before we get started,
      you'll have to confirm your email address.
    example_title: newsletter
  - text: >-
      Hi <NAME>,


      I hope this email finds you well. I wanted to reach out and ask about
      office hours
    example_title: office hours
  - text: >-
      Greetings <NAME>,


      I hope you had a splendid evening at the Company sausage eating festival.
      I am reaching out because
    example_title: festival
  - text: |-
      Good Morning Harold,

      I was wondering when the next
    example_title: event
  - text: URGENT - I need the TPS reports
    example_title: URGENT
  - text: |-
      Hi Archibald,

      I hope this email finds you extremely well.
    example_title: emails that find you
  - text: |-
      Hello there.

      I just wanted to reach out and check in to
    example_title: checking in
  - text: >-
      Hello <NAME>,


      I hope this email finds you well. I wanted to reach out and see if you've
      enjoyed your time with us
    example_title: work well
  - text: >-
      Hi <NAME>,


      I hope this email finds you well. I wanted to reach out and see if we
      could catch up
    example_title: catch up
  - text: >-
      I'm <NAME> and I just moved into the area and wanted to reach out and get
      some details on where I could get groceries and
    example_title: grocery
parameters:
  min_length: 4
  max_length: 128
  length_penalty: 0.8
  no_repeat_ngram_size: 2
  do_sample: false
  num_beams: 8
  early_stopping: true
  repetition_penalty: 5.5

distilgpt2-emailgen: V2

This is a V2, which should perform better than V1. This is in the process of being evaluated.

Why write the rest of your email when you can generate it?

from transformers import pipeline

model_tag = "postbot/distilgpt2-emailgen-V2"
generator = pipeline(
              'text-generation', 
              model=model_tag, 
            )
            
prompt = """
Hello, 

Following up on the bubblegum shipment."""

result = generator(
    prompt,
    max_length=64,
    do_sample=False,
    early_stopping=True,
) # generate
print(result[0]['generated_text'])

Model description

This model is a fine-tuned version of distilgpt2 on the postbot/multi-emails-100k dataset. It achieves the following results on the evaluation set:

• Loss: 1.9126

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters (run 1/2)

TODO

Training hyperparameters (run 2/2)

The following hyperparameters were used during training:

• learning_rate: 0.0006
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• distributed_type: multi-GPU
• gradient_accumulation_steps: 8
• total_train_batch_size: 128
• 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

Training Loss	Epoch	Step	Validation Loss
1.9045	1.0	789	2.0006
1.8115	2.0	1578	1.9557
1.8501	3.0	2367	1.9110
1.7376	4.0	3156	1.9126

Framework versions

• Transformers 4.22.2
• Pytorch 1.10.0+cu113
• Datasets 2.5.1
• Tokenizers 0.12.1