readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: MTL-roberta-base
    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-roberta-base
  
  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.4859
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|
  | 1.8338        | 1.0   | 98   | 1.6750          |
  | 1.7732        | 2.0   | 196  | 1.6229          |
  | 1.7208        | 3.0   | 294  | 1.6131          |
  | 1.6917        | 4.0   | 392  | 1.5936          |
  | 1.6579        | 5.0   | 490  | 1.6183          |
  | 1.6246        | 6.0   | 588  | 1.6015          |
  | 1.6215        | 7.0   | 686  | 1.5248          |
  | 1.5743        | 8.0   | 784  | 1.5454          |
  | 1.5621        | 9.0   | 882  | 1.5925          |
  | 1.5652        | 10.0  | 980  | 1.5213          |
  | 1.5615        | 11.0  | 1078 | 1.4845          |
  | 1.5349        | 12.0  | 1176 | 1.5443          |
  | 1.5165        | 13.0  | 1274 | 1.5304          |
  | 1.5164        | 14.0  | 1372 | 1.4773          |
  | 1.5293        | 15.0  | 1470 | 1.5537          |
  
  
  ### Framework versions
  
  - Transformers 4.16.2
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.3
  - Tokenizers 0.11.0
  