readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: PELM-JointGPT2
    results: []
  ---
  
  <!-- 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. -->
  
  # PELM-JointGPT2
  
  This model is based on PELM framework and initialised from [genGPT-2](https://huggingface.co/GItaf/GPT2-LM-Finetuned-MBTI), then fine-tuned on the [MBTI dataset](https://www.kaggle.com/datasets/datasnaek/mbti-type).
  It achieves the following results on the evaluation set:
  - Loss: 4.3556
  - Cls loss: 1.5778
  - Lm loss: 3.9609
  - Cls Accuracy: 0.6202
  - Cls F1: 0.6126
  - Cls Precision: 0.6216
  - Cls Recall: 0.6202
  - Perplexity: 52.50
  
  ## 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: 2e-05
  - train_batch_size: 2
  - eval_batch_size: 2
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Cls loss | Lm loss | Cls Accuracy | Cls F1 | Cls Precision | Cls Recall | Perplexity |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------:|:------------:|:------:|:-------------:|:----------:|:----------:|
  | 4.2735        | 1.0   | 3470  | 4.3562          | 1.5844   | 3.9598  | 0.5833       | 0.5708 | 0.5928        | 0.5833     | 52.45      |
  | 4.0754        | 2.0   | 6940  | 4.3295          | 1.4806   | 3.9590  | 0.6196       | 0.6113 | 0.6332        | 0.6196     | 52.41      |
  | 3.985         | 3.0   | 10410 | 4.3556          | 1.5778   | 3.9609  | 0.6202       | 0.6126 | 0.6216        | 0.6202     | 52.50      |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1
  - Datasets 2.4.0
  - Tokenizers 0.12.1