readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: hasoc19-microsoft-mdeberta-v3-base-HatredStatement-new
    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. -->
  
  # hasoc19-microsoft-mdeberta-v3-base-HatredStatement-new
  
  This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6039
  - Accuracy: 0.7329
  - Precision: 0.7324
  - Recall: 0.7329
  - F1: 0.7316
  
  ## 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: 1e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 6
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | No log        | 1.0   | 296  | 0.5276          | 0.7253   | 0.7258    | 0.7253 | 0.7225 |
  | 0.5406        | 2.0   | 592  | 0.5513          | 0.7319   | 0.7348    | 0.7319 | 0.7278 |
  | 0.5406        | 3.0   | 888  | 0.5466          | 0.7357   | 0.7458    | 0.7357 | 0.7283 |
  | 0.4372        | 4.0   | 1184 | 0.5531          | 0.7452   | 0.7502    | 0.7452 | 0.7406 |
  | 0.4372        | 5.0   | 1480 | 0.5927          | 0.7367   | 0.7364    | 0.7367 | 0.7352 |
  | 0.3868        | 6.0   | 1776 | 0.6039          | 0.7329   | 0.7324    | 0.7329 | 0.7316 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0.dev0
  - Pytorch 1.11.0+cu102
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  