readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: MTL-bert-base-uncased-ww
    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. -->
  
  # MTL-bert-base-uncased-ww
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.5261
  
  ## 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: 7
  - eval_batch_size: 7
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 15
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 3.2964        | 1.0   | 99   | 2.9560          |
  | 3.0419        | 2.0   | 198  | 2.8336          |
  | 2.8979        | 3.0   | 297  | 2.8009          |
  | 2.8815        | 4.0   | 396  | 2.7394          |
  | 2.8373        | 5.0   | 495  | 2.6813          |
  | 2.741         | 6.0   | 594  | 2.6270          |
  | 2.6877        | 7.0   | 693  | 2.5216          |
  | 2.6823        | 8.0   | 792  | 2.5485          |
  | 2.6326        | 9.0   | 891  | 2.5690          |
  | 2.5976        | 10.0  | 990  | 2.6336          |
  | 2.6009        | 11.0  | 1089 | 2.5919          |
  | 2.5615        | 12.0  | 1188 | 2.4264          |
  | 2.5826        | 13.0  | 1287 | 2.5562          |
  | 2.5693        | 14.0  | 1386 | 2.5529          |
  | 2.5494        | 15.0  | 1485 | 2.5300          |
  
  
  ### Framework versions
  
  - Transformers 4.16.2
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.3
  - Tokenizers 0.11.0
  