readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: xlm-roberta-base-finetuned-emotion-17-labels
    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. -->
  
  # xlm-roberta-base-finetuned-emotion-17-labels
  
  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.4087
  - Accuracy: 0.6495
  - F1: 0.6481
  
  ## 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: 15
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 2.5228        | 1.0   | 177  | 2.0913          | 0.3364   | 0.3043 |
  | 1.9362        | 2.0   | 354  | 1.7457          | 0.4353   | 0.4037 |
  | 1.5719        | 3.0   | 531  | 1.4817          | 0.5244   | 0.5068 |
  | 1.2558        | 4.0   | 708  | 1.3574          | 0.5654   | 0.5556 |
  | 1.024         | 5.0   | 885  | 1.3139          | 0.5880   | 0.5788 |
  | 0.8271        | 6.0   | 1062 | 1.3123          | 0.5922   | 0.5856 |
  | 0.6645        | 7.0   | 1239 | 1.2887          | 0.6099   | 0.6067 |
  | 0.5478        | 8.0   | 1416 | 1.3263          | 0.6226   | 0.6201 |
  | 0.442         | 9.0   | 1593 | 1.3239          | 0.6346   | 0.6313 |
  | 0.3647        | 10.0  | 1770 | 1.3360          | 0.6276   | 0.6241 |
  | 0.2957        | 11.0  | 1947 | 1.3942          | 0.6325   | 0.6280 |
  | 0.2534        | 12.0  | 2124 | 1.3962          | 0.6403   | 0.6397 |
  | 0.2191        | 13.0  | 2301 | 1.4120          | 0.6417   | 0.6399 |
  | 0.1918        | 14.0  | 2478 | 1.3978          | 0.6431   | 0.6427 |
  | 0.1728        | 15.0  | 2655 | 1.4087          | 0.6495   | 0.6481 |
  
  
  ### Framework versions
  
  - Transformers 4.19.0
  - Pytorch 1.12.1+cu113
  - Datasets 1.16.1
  - Tokenizers 0.12.1
  