readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: flan-t5-xl-finetuned-unnatural-instructions
    results: []
  
  widget:
  - text: "You will be provided with a short text that you should read. After reading the text, answer the question 'Who is telling the story in first person?'\nText: I went to the store and bought some milk.\nThe output should be one of the two options: 'I' or 'Not I'.\nOutput:"
  - text: "You are given the title and opening paragraph of an article. Your task is to find the main idea of the article using context clues from the text.\nText: The first confirmed case of Zika in Africa has been found in Uganda, health officials said on Tuesday, more than 4,000 miles away from Brazil where a major outbreak began last year.\nAblood test carried out at a private hospital showed that a five-year-old girl who had returned from Mozambique three weeks ago had contracted Zika, which can cause birth defects in babies born to infected mothers.\nOutput:"
  - text: "We have given you a list of sentences. Your task is to go through this list and find all the unique words used in these sentences and store them in a dictionary.\nThis is an example sentence., That is another example sentence., Here is an interesting sentence!\nThe output should be a Python dictionary with keys as the unique words and values as the number of times that word occurs in the text.\nOutput:\n"
  - text: "You will given a set of two or more words. Output the shortest word in the set. If there is a tie for the shortest word, output all tied words in alphabetical order, separated by space.\nWords: defenestrate, circumambulate, excommunication.\nThe input will be lowercase and only contain alphanumeric characters and spaces.\nOutput:\n"
  
  inference:
    parameters:
      max_length: 150
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # flan-t5-xl-finetuned-unnatural-instructions
  
  This model is a fine-tuned version of [google/flan-t5-xl](https://huggingface.co/google/flan-t5-xl) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1224
  
  ## 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: 5e-05
  - train_batch_size: 1
  - eval_batch_size: 2
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - training_steps: 5000
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 0.1345        | 0.02  | 1000 | 0.1386          |
  | 0.14          | 0.03  | 2000 | 0.1336          |
  | 0.1402        | 0.05  | 3000 | 0.1282          |
  | 0.129         | 0.07  | 4000 | 0.1235          |
  | 0.1356        | 0.08  | 5000 | 0.1224          |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  