readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: twitter-data-xlm-roberta-base-sentiment-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. -->
  
  # twitter-data-xlm-roberta-base-sentiment-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: 0.2455
  - Accuracy: 0.9327
  - Precision: 0.9333
  - Recall: 0.9327
  - F1: 0.9328
  
  ## 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: 1e-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: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.3851        | 1.0   | 1783  | 0.3286          | 0.8998   | 0.9005    | 0.8998 | 0.8997 |
  | 0.2812        | 2.0   | 3566  | 0.2624          | 0.9217   | 0.9224    | 0.9217 | 0.9216 |
  | 0.2501        | 3.0   | 5349  | 0.2550          | 0.9227   | 0.9252    | 0.9227 | 0.9231 |
  | 0.2272        | 4.0   | 7132  | 0.2458          | 0.9268   | 0.9269    | 0.9268 | 0.9265 |
  | 0.2101        | 5.0   | 8915  | 0.2441          | 0.9327   | 0.9334    | 0.9327 | 0.9327 |
  | 0.1966        | 6.0   | 10698 | 0.2367          | 0.9311   | 0.9312    | 0.9311 | 0.9309 |
  | 0.1822        | 7.0   | 12481 | 0.2346          | 0.9329   | 0.9334    | 0.9329 | 0.9329 |
  | 0.1702        | 8.0   | 14264 | 0.2319          | 0.9343   | 0.9351    | 0.9343 | 0.9344 |
  | 0.1615        | 9.0   | 16047 | 0.2426          | 0.9328   | 0.9336    | 0.9328 | 0.9329 |
  | 0.1536        | 10.0  | 17830 | 0.2455          | 0.9327   | 0.9333    | 0.9327 | 0.9328 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0.dev0
  - Pytorch 1.11.0+cu102
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  