readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: sentiment-5Epochs
    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-5Epochs
  
  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: 0.4947
  - Accuracy: 0.8719
  - F1: 0.8685
  - Precision: 0.8919
  - Recall: 0.8463
  
  ## 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
  | 0.3566        | 1.0   | 7088  | 0.3987          | 0.8627   | 0.8505 | 0.9336    | 0.7810 |
  | 0.3468        | 2.0   | 14176 | 0.3861          | 0.8702   | 0.8638 | 0.9085    | 0.8232 |
  | 0.335         | 3.0   | 21264 | 0.4421          | 0.8759   | 0.8697 | 0.9154    | 0.8283 |
  | 0.3003        | 4.0   | 28352 | 0.4601          | 0.8754   | 0.8696 | 0.9119    | 0.8311 |
  | 0.2995        | 5.0   | 35440 | 0.4947          | 0.8719   | 0.8685 | 0.8919    | 0.8463 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  