readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - matthews_correlation
  model-index:
  - name: TestMeanFraction2
    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. -->
  
  # TestMeanFraction2
  
  This model is a fine-tuned version of [cmarkea/distilcamembert-base](https://huggingface.co/cmarkea/distilcamembert-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.3967
  - Matthews Correlation: 0.2537
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  "La panique totale" Cette femme trouve une énorme araignée suspendue à sa douche.
  
  ## Training and evaluation data
  
  More information needed
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 5e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 8
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
  |:-------------:|:-----:|:----:|:---------------:|:--------------------:|
  | No log        | 0.13  | 50   | 1.1126          | 0.1589               |
  | No log        | 0.25  | 100  | 1.0540          | 0.1884               |
  | No log        | 0.38  | 150  | 1.1533          | 0.0818               |
  | No log        | 0.51  | 200  | 1.0676          | 0.1586               |
  | No log        | 0.64  | 250  | 0.9949          | 0.2280               |
  | No log        | 0.76  | 300  | 1.0343          | 0.2629               |
  | No log        | 0.89  | 350  | 1.0203          | 0.2478               |
  | No log        | 1.02  | 400  | 1.0041          | 0.2752               |
  | No log        | 1.15  | 450  | 1.0808          | 0.2256               |
  | 1.023         | 1.27  | 500  | 1.0029          | 0.2532               |
  | 1.023         | 1.4   | 550  | 1.0204          | 0.2508               |
  | 1.023         | 1.53  | 600  | 1.1377          | 0.1689               |
  | 1.023         | 1.65  | 650  | 1.0499          | 0.2926               |
  | 1.023         | 1.78  | 700  | 1.0441          | 0.2474               |
  | 1.023         | 1.91  | 750  | 1.0279          | 0.2611               |
  | 1.023         | 2.04  | 800  | 1.1511          | 0.2804               |
  | 1.023         | 2.16  | 850  | 1.2381          | 0.2512               |
  | 1.023         | 2.29  | 900  | 1.3340          | 0.2385               |
  | 1.023         | 2.42  | 950  | 1.4372          | 0.2842               |
  | 0.7325        | 2.54  | 1000 | 1.3967          | 0.2537               |
  | 0.7325        | 2.67  | 1050 | 1.4272          | 0.2624               |
  | 0.7325        | 2.8   | 1100 | 1.3869          | 0.1941               |
  | 0.7325        | 2.93  | 1150 | 1.4983          | 0.2063               |
  | 0.7325        | 3.05  | 1200 | 1.4959          | 0.2409               |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0a0+0aef44c
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  