readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: sentiment-10Epochs
    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. -->
  
  # sentiment-10Epochs
  
  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7030
  - Accuracy: 0.8603
  - F1: 0.8585
  - Precision: 0.8699
  - Recall: 0.8473
  
  ## 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: 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: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
  | 0.3645        | 1.0   | 7088  | 0.4315          | 0.8603   | 0.8466 | 0.9386    | 0.7711 |
  | 0.374         | 2.0   | 14176 | 0.4015          | 0.8713   | 0.8648 | 0.9105    | 0.8235 |
  | 0.3363        | 3.0   | 21264 | 0.4772          | 0.8705   | 0.8615 | 0.9256    | 0.8057 |
  | 0.3131        | 4.0   | 28352 | 0.4579          | 0.8702   | 0.8650 | 0.9007    | 0.8321 |
  | 0.3097        | 5.0   | 35440 | 0.4160          | 0.8721   | 0.8663 | 0.9069    | 0.8292 |
  | 0.2921        | 6.0   | 42528 | 0.4638          | 0.8673   | 0.8630 | 0.8917    | 0.8362 |
  | 0.2725        | 7.0   | 49616 | 0.5183          | 0.8654   | 0.8602 | 0.8947    | 0.8283 |
  | 0.2481        | 8.0   | 56704 | 0.5846          | 0.8649   | 0.8624 | 0.8787    | 0.8467 |
  | 0.192         | 9.0   | 63792 | 0.6481          | 0.8610   | 0.8596 | 0.8680    | 0.8514 |
  | 0.1945        | 10.0  | 70880 | 0.7030          | 0.8603   | 0.8585 | 0.8699    | 0.8473 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  