readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: output_mlm
    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. -->
  
  # output_mlm
  
  This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.2024
  
  ## 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: 5e-05
  - train_batch_size: 16
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3.0
  
  ### Training results
  
  | Training Loss | Epoch | Step   | Validation Loss |
  |:-------------:|:-----:|:------:|:---------------:|
  | 1.5832        | 0.19  | 15000  | 1.4992          |
  | 1.5325        | 0.39  | 30000  | 1.4653          |
  | 1.4979        | 0.58  | 45000  | 1.4359          |
  | 1.4715        | 0.77  | 60000  | 1.4039          |
  | 1.4448        | 0.97  | 75000  | 1.3877          |
  | 1.4191        | 1.16  | 90000  | 1.3603          |
  | 1.3988        | 1.35  | 105000 | 1.3425          |
  | 1.3699        | 1.54  | 120000 | 1.3230          |
  | 1.3493        | 1.74  | 135000 | 1.3012          |
  | 1.3201        | 1.93  | 150000 | 1.2773          |
  | 1.2993        | 2.12  | 165000 | 1.2617          |
  | 1.2745        | 2.32  | 180000 | 1.2490          |
  | 1.2614        | 2.51  | 195000 | 1.2283          |
  | 1.2424        | 2.7   | 210000 | 1.2152          |
  | 1.2296        | 2.9   | 225000 | 1.2052          |
  
  
  ### Framework versions
  
  - Transformers 4.11.2
  - Pytorch 1.9.0
  - Datasets 1.12.1
  - Tokenizers 0.10.3
  