readme: ---
  language:
  - en
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - accuracy
  model-index:
  - name: randomcomb_mlm_ep5_mnli
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: GLUE MNLI
        type: glue
        args: mnli
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.8615744507729862
  ---
  
  <!-- 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. -->
  
  # randomcomb_mlm_ep5_mnli
  
  This model is a fine-tuned version of [cuenb](https://huggingface.co/joey234/cuenb) on the GLUE MNLI dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4416
  - Accuracy: 0.8616
  
  ## 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: 3e-05
  - train_batch_size: 32
  - eval_batch_size: 16
  - seed: 42
  - 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 | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 0.5569        | 0.41  | 5000  | 0.4415          | 0.8273   |
  | 0.4598        | 0.81  | 10000 | 0.4234          | 0.8425   |
  | 0.3832        | 1.22  | 15000 | 0.4398          | 0.8475   |
  | 0.3314        | 1.63  | 20000 | 0.4137          | 0.8494   |
  | 0.3158        | 2.04  | 25000 | 0.4484          | 0.8527   |
  | 0.2294        | 2.44  | 30000 | 0.4471          | 0.8552   |
  | 0.2283        | 2.85  | 35000 | 0.4541          | 0.8557   |
  
  
  ### Framework versions
  
  - Transformers 4.21.0.dev0
  - Pytorch 1.8.0
  - Datasets 1.18.3
  - Tokenizers 0.12.1
  