readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  model-index:
  - name: camembert-base-cae-emotion
    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. -->
  
  # camembert-base-cae-emotion
  
  This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7867
  - Precision: 0.7824
  - Recall: 0.7757
  - F1: 0.7757
  
  ## 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: 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
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 10.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
  | 1.9198        | 1.0   | 54   | 1.4555          | 0.2097    | 0.4579 | 0.2877 |
  | 1.3396        | 2.0   | 108  | 1.2146          | 0.2097    | 0.4579 | 0.2877 |
  | 1.1006        | 3.0   | 162  | 0.9712          | 0.6010    | 0.6449 | 0.6054 |
  | 0.7635        | 4.0   | 216  | 0.8224          | 0.6939    | 0.7290 | 0.7057 |
  | 0.4785        | 5.0   | 270  | 0.7867          | 0.7824    | 0.7757 | 0.7757 |
  | 0.3129        | 6.0   | 324  | 0.8196          | 0.7882    | 0.7570 | 0.7625 |
  | 0.2016        | 7.0   | 378  | 0.9116          | 0.8078    | 0.7009 | 0.7295 |
  | 0.1395        | 8.0   | 432  | 0.9277          | 0.7536    | 0.7103 | 0.7219 |
  | 0.121         | 9.0   | 486  | 0.9636          | 0.7626    | 0.7290 | 0.7367 |
  | 0.0936        | 10.0  | 540  | 0.9722          | 0.8005    | 0.7383 | 0.7542 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  