readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - pawsx
  metrics:
  - accuracy
  - f1
  model-index:
  - name: camembert-base-finetuned-paraphrase
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: pawsx
        type: pawsx
        args: fr
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.9085
      - name: F1
        type: f1
        value: 0.9088724090678741
  ---
  
  <!-- 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. -->
  
  # camembert-base-finetuned-paraphrase
  
  This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on the pawsx dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2708
  - Accuracy: 0.9085
  - F1: 0.9089
  
  ## 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: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 4
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.3918        | 1.0   | 772  | 0.3211          | 0.869    | 0.8696 |
  | 0.2103        | 2.0   | 1544 | 0.2448          | 0.9075   | 0.9077 |
  | 0.1622        | 3.0   | 2316 | 0.2577          | 0.9055   | 0.9059 |
  | 0.1344        | 4.0   | 3088 | 0.2708          | 0.9085   | 0.9089 |
  
  
  ### Framework versions
  
  - Transformers 4.19.3
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  