readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: twitter-data-xlm-roberta-base-eng-only-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-eng-only-sentiment-finetuned-memes
  
  This model is a fine-tuned version of [jayantapaul888/twitter-data-xlm-roberta-base-sentiment-finetuned-memes](https://huggingface.co/jayantapaul888/twitter-data-xlm-roberta-base-sentiment-finetuned-memes) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6286
  - Accuracy: 0.8660
  - Precision: 0.8796
  - Recall: 0.8795
  - F1: 0.8795
  
  ## 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  | 0.3421          | 0.8407   | 0.8636    | 0.8543 | 0.8553 |
  | 0.396         | 2.0   | 756  | 0.3445          | 0.8496   | 0.8726    | 0.8634 | 0.8631 |
  | 0.2498        | 3.0   | 1134 | 0.3656          | 0.8585   | 0.8764    | 0.8727 | 0.8723 |
  | 0.1543        | 4.0   | 1512 | 0.4549          | 0.8600   | 0.8742    | 0.8740 | 0.8741 |
  | 0.1543        | 5.0   | 1890 | 0.5932          | 0.8645   | 0.8783    | 0.8780 | 0.8780 |
  | 0.0815        | 6.0   | 2268 | 0.6286          | 0.8660   | 0.8796    | 0.8795 | 0.8795 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0.dev0
  - Pytorch 1.11.0+cu102
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  