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: HATEXPLAIN
        type: ''
        args: hatexplain
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.4162330905306972
  ---
  
  <!-- 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 HATEXPLAIN dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7667
  - Accuracy: 0.4162
  - Accuracy 0: 0.8145
  - Accuracy 1: 0.1895
  - Accuracy 2: 0.3084
  
  ## 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: 150
  - num_epochs: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Accuracy 0 | Accuracy 1 | Accuracy 2 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:----------:|:----------:|:----------:|
  | No log        | 1.0   | 481  | 0.7431          | 0.4152   | 0.7707     | 0.1805     | 0.3650     |
  | No log        | 2.0   | 962  | 0.7346          | 0.4152   | 0.8010     | 0.2190     | 0.2774     |
  | No log        | 3.0   | 1443 | 0.7667          | 0.4162   | 0.8145     | 0.1895     | 0.3084     |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.11.6
  