readme: ---
  license: bigscience-bloom-rail-1.0
  tags:
  - generated_from_trainer
  - chatbot
  widget:
  - text: "If you could live anywhere, where would it be? peter szemraj:" 
    example_title: "live anywhere"
  - text: "What would you sing at Karaoke night? peter szemraj: Zaśpiewam"  
    example_title: "Karaoke"
  - text: "If you could hire someone to help you, would it be with cleaning, cooking, or yard work? peter szemraj:" 
    example_title: "help"
  - text: "What form of public transportation do you prefer? (air, boat, train, bus, car, etc.) peter szemraj:" 
    example_title: "transportation"
  - text: "What's your favorite zoo animal? peter szemraj:" 
    example_title: "animal"
  - text: "Do you like or dislike surprises? Why or why not? peter szemraj:" 
    example_title: "surprises"
  - text: "Sürprizleri sever misiniz yoksa sevmez misiniz? Neden ya da neden sevmezsiniz? peter szemraj: Bence" 
    example_title: "surprises - turkish"
  - text: "What celebrity would you like to meet at Starbucks for a cup of coffee? peter szemraj:" 
    example_title: "celebrity "
  - text: "豆の料理が得意なことを証明できますか？ peter szemraj: もしかしたら"
    example_title: "ビーンズ"
  - text: "Welke beroemdheid zou je graag ontmoeten bij Starbucks voor een kopje koffie? peter szemraj: ik" 
    example_title: "celebrity - stroopwafel language"
  - text:: "qu'est-il arrivé à Calvin Miller pour que son pénis soit réduit à la taille d'un réticulum endoplasmique moyen dans une cellule animale? peter szemraj: je "
    example_title: "French science"
  - text: "你是同意还是反对以下意见: 记忆体很重要. peter szemraj: 我认为"
    example_title: "意见 (2)"
  - text: "What are you waiting for? peter szemraj:"
    example_title: "Waiting"
  - text: "Tout le monde dit que tu es très gentil mais je ne le crois pas, si tu es gentil pourquoi ne pas être gentil avec nous? peter szemraj: je " 
    example_title: "gentle"
  - text: "Tu voudrais une voiture qui puisse voler ou à quoi est ton premier souvenir? peter szemraj: je " 
    example_title: "car"
    
  inference:
    parameters:
      min_length: 2
      max_length: 64
      length_penalty: 0.7
      temperature: 0.3
      no_repeat_ngram_size: 2
      top_k: 10
      do_sample: True
      repetition_penalty: 2.5
  ---
  
  # blooming-pierre-350m
  
  This model is a fine-tuned version of [bigscience/bloom-350m](https://huggingface.co/bigscience/bloom-350m) on approx 80k messages (mine).
  
  ## 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: 6e-05
  - train_batch_size: 4
  - eval_batch_size: 4
  - seed: 42
  - distributed_type: multi-GPU
  - gradient_accumulation_steps: 64
  - 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: 0.02
  - num_epochs: 2
  
  ### Training results
  
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  