readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: SEED0042
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: MNLI
        type: ''
        args: mnli
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.8879266428935303
  ---
  
  <!-- 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. -->
  
  # SEED0042
  
  This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on the MNLI dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4265
  - Accuracy: 0.8879
  
  ## 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: 32
  - seed: 42
  - distributed_type: not_parallel
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 2000
  - num_epochs: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 0.3762        | 1.0   | 12272 | 0.3312          | 0.8794   |
  | 0.2542        | 2.0   | 24544 | 0.3467          | 0.8843   |
  | 0.1503        | 3.0   | 36816 | 0.4265          | 0.8879   |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.11.6
  