readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: smalldata-prosusai-finbert-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. -->
  
  # smalldata-prosusai-finbert-eng-only-sentiment-single-finetuned-memes
  
  This model is a fine-tuned version of [jayantapaul888/twitter-data-prosusai-finbert-sentiment-finetuned-memes](https://huggingface.co/jayantapaul888/twitter-data-prosusai-finbert-sentiment-finetuned-memes) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9617
  - Accuracy: 0.8526
  - Precision: 0.8668
  - Recall: 0.8673
  - F1: 0.8667
  
  ## 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  | 0.3208          | 0.8608   | 0.8779    | 0.8737 | 0.8738 |
  | 0.365         | 2.0   | 756  | 0.3473          | 0.8533   | 0.8674    | 0.8677 | 0.8675 |
  | 0.1528        | 3.0   | 1134 | 0.5630          | 0.8414   | 0.8602    | 0.8577 | 0.8564 |
  | 0.054         | 4.0   | 1512 | 0.7227          | 0.8496   | 0.8674    | 0.8649 | 0.8644 |
  | 0.054         | 5.0   | 1890 | 0.9199          | 0.8555   | 0.8703    | 0.8701 | 0.8695 |
  | 0.0156        | 6.0   | 2268 | 0.9617          | 0.8526   | 0.8668    | 0.8673 | 0.8667 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0.dev0
  - Pytorch 1.11.0+cu102
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  