readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: xlm-roberta-base-eng-only-sentiment-single-finetuned-memes
    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-eng-only-sentiment-single-finetuned-memes
  
  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: 0.5629
  - Accuracy: 0.8652
  - Precision: 0.8794
  - Recall: 0.8786
  - F1: 0.8789
  
  ## 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: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 6
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | No log        | 1.0   | 378  | 0.3506          | 0.8459   | 0.8647    | 0.8584 | 0.8605 |
  | 0.4424        | 2.0   | 756  | 0.3264          | 0.8563   | 0.8818    | 0.8696 | 0.8689 |
  | 0.2888        | 3.0   | 1134 | 0.3563          | 0.8578   | 0.8759    | 0.8701 | 0.8714 |
  | 0.1889        | 4.0   | 1512 | 0.3939          | 0.8585   | 0.8733    | 0.8729 | 0.8730 |
  | 0.1889        | 5.0   | 1890 | 0.4698          | 0.8622   | 0.8765    | 0.8761 | 0.8763 |
  | 0.1136        | 6.0   | 2268 | 0.5629          | 0.8652   | 0.8794    | 0.8786 | 0.8789 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0.dev0
  - Pytorch 1.11.0+cu102
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  