readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: BERT-FINETUNE-MBTI-LM-BERT-FINETUNE-MBTI-LM-JointBERT-Warmup-from-LM
    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. -->
  
  # BERT-FINETUNE-MBTI-LM-BERT-FINETUNE-MBTI-LM-JointBERT-Warmup-from-LM
  
  This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 4.7966
  - Cls loss: 1.4255
  - Lm loss: 4.4398
  - Cls Accuracy: 0.6380
  - Cls F1: 0.6319
  - Cls Precision: 0.6416
  - Cls Recall: 0.6380
  - Perplexity: 84.76
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------:|:------------:|:------:|:-------------:|:----------:|:----------:|
  | 5.3087        | 1.0   | 3470  | 4.9005          | 1.4109   | 4.5474  | 0.6075       | 0.5981 | 0.6132        | 0.6075     | 94.39      |
  | 4.8274        | 2.0   | 6940  | 4.7987          | 1.3448   | 4.4621  | 0.6242       | 0.6193 | 0.6381        | 0.6242     | 86.67      |
  | 4.6472        | 3.0   | 10410 | 4.7966          | 1.4255   | 4.4398  | 0.6380       | 0.6319 | 0.6416        | 0.6380     | 84.76      |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1
  - Datasets 2.4.0
  - Tokenizers 0.12.1