readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: Homophobia-Transphobia-v2-mBERT-EDA
    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. -->
  
  # Homophobia-Transphobia-v2-mBERT-EDA
  
  This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5401
  - Accuracy: 0.9317
  - F1: 0.4498
  
  ## 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: 2e-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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.1699        | 1.0   | 189  | 0.4125          | 0.9229   | 0.4634 |
  | 0.0387        | 2.0   | 378  | 0.4658          | 0.9229   | 0.3689 |
  | 0.0148        | 3.0   | 567  | 0.5250          | 0.9355   | 0.4376 |
  | 0.0005        | 4.0   | 756  | 0.5336          | 0.9317   | 0.4531 |
  | 0.0016        | 5.0   | 945  | 0.5401          | 0.9317   | 0.4498 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.4
  - Tokenizers 0.11.6
  