README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
  - text generation
  - 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: 32
  max_length: 128
  no_repeat_ngram_size: 2
  do_sample: true
  temperature: 0.4
  top_k: 30
  top_p: 0.9
  repetition_penalty: 3.5
  length_penalty: 0.9
base_model: EleutherAI/gpt-neo-1.3B
model-index:
  - name: gpt-neo-1.3B-emailgen
    results:
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: AI2 Reasoning Challenge (25-Shot)
          type: ai2_arc
          config: ARC-Challenge
          split: test
          args:
            num_few_shot: 25
        metrics:
          - type: acc_norm
            value: 29.95
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=postbot/gpt-neo-1.3B-emailgen
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: HellaSwag (10-Shot)
          type: hellaswag
          split: validation
          args:
            num_few_shot: 10
        metrics:
          - type: acc_norm
            value: 47.95
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=postbot/gpt-neo-1.3B-emailgen
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MMLU (5-Shot)
          type: cais/mmlu
          config: all
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 24.11
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=postbot/gpt-neo-1.3B-emailgen
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: TruthfulQA (0-shot)
          type: truthful_qa
          config: multiple_choice
          split: validation
          args:
            num_few_shot: 0
        metrics:
          - type: mc2
            value: 42.55
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=postbot/gpt-neo-1.3B-emailgen
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: Winogrande (5-shot)
          type: winogrande
          config: winogrande_xl
          split: validation
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 56.27
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=postbot/gpt-neo-1.3B-emailgen
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: GSM8k (5-shot)
          type: gsm8k
          config: main
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 0
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=postbot/gpt-neo-1.3B-emailgen
          name: Open LLM Leaderboard

gpt-neo-1.3B-emailgen

This model is a fine-tuned version of EleutherAI/gpt-neo-1.3B on the postbot/multi-emails-100k dataset. It achieves the following results on the evaluation set:

• Loss: 1.6930

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: 4
• eval_batch_size: 4
• seed: 42
• distributed_type: multi-GPU
• gradient_accumulation_steps: 32
• 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: 0.02
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss
1.8669	1.0	789	1.7866
1.4049	2.0	1578	1.6930

Framework versions

• Transformers 4.22.2
• Pytorch 1.10.0+cu113
• Tokenizers 0.12.1

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	33.47
AI2 Reasoning Challenge (25-Shot)	29.95
HellaSwag (10-Shot)	47.95
MMLU (5-Shot)	24.11
TruthfulQA (0-shot)	42.55
Winogrande (5-shot)	56.27
GSM8k (5-shot)	0.00