readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - wikitext
  metrics:
  - accuracy
  model-index:
  - name: distilbert_add_pre-training-dim-96
    results:
    - task:
        name: Masked Language Modeling
        type: fill-mask
      dataset:
        name: wikitext wikitext-103-raw-v1
        type: wikitext
        config: wikitext-103-raw-v1
        split: validation
        args: wikitext-103-raw-v1
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.14942141332434558
  ---
  
  <!-- 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. -->
  
  # distilbert_add_pre-training-dim-96
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the wikitext wikitext-103-raw-v1 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 6.6092
  - Accuracy: 0.1494
  
  ## 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: 64
  - eval_batch_size: 64
  - seed: 10
  - distributed_type: multi-GPU
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 100
  - num_epochs: 15
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 14.685        | 1.0   | 3573  | 9.3922          | 0.1240   |
  | 8.0255        | 2.0   | 7146  | 7.1510          | 0.1315   |
  | 7.0152        | 3.0   | 10719 | 6.7861          | 0.1482   |
  | 6.8127        | 4.0   | 14292 | 6.7053          | 0.1493   |
  | 6.74          | 5.0   | 17865 | 6.6695          | 0.1474   |
  | 6.7067        | 6.0   | 21438 | 6.6431          | 0.1491   |
  | 6.6871        | 7.0   | 25011 | 6.6204          | 0.1483   |
  | 6.6748        | 8.0   | 28584 | 6.6250          | 0.1473   |
  | 6.6649        | 9.0   | 32157 | 6.6108          | 0.1486   |
  | 6.6596        | 10.0  | 35730 | 6.6140          | 0.1497   |
  | 6.6536        | 11.0  | 39303 | 6.6067          | 0.1493   |
  | 6.6483        | 12.0  | 42876 | 6.6140          | 0.1489   |
  | 6.6463        | 13.0  | 46449 | 6.6096          | 0.1484   |
  | 6.6434        | 14.0  | 50022 | 6.5570          | 0.1526   |
  | 6.6414        | 15.0  | 53595 | 6.5836          | 0.1526   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  