readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: MTL-distilbert-base-uncased
    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-distilbert-base-uncased
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.0874
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|
  | 2.5593        | 1.0   | 99   | 2.3163          |
  | 2.4346        | 2.0   | 198  | 2.2918          |
  | 2.3377        | 3.0   | 297  | 2.2345          |
  | 2.2953        | 4.0   | 396  | 2.1463          |
  | 2.2296        | 5.0   | 495  | 2.1761          |
  | 2.2235        | 6.0   | 594  | 2.0721          |
  | 2.1878        | 7.0   | 693  | 2.1460          |
  | 2.1569        | 8.0   | 792  | 2.0856          |
  | 2.1455        | 9.0   | 891  | 2.1039          |
  | 2.1391        | 10.0  | 990  | 2.1112          |
  | 2.1056        | 11.0  | 1089 | 2.0694          |
  | 2.1076        | 12.0  | 1188 | 2.0501          |
  | 2.0919        | 13.0  | 1287 | 2.0484          |
  | 2.0669        | 14.0  | 1386 | 2.0342          |
  | 2.0595        | 15.0  | 1485 | 2.0802          |
  
  
  ### Framework versions
  
  - Transformers 4.16.2
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.3
  - Tokenizers 0.11.0
  