readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: twitter-data-distilbert-base-uncased-sentiment-finetuned-memes-test
    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-distilbert-base-uncased-sentiment-finetuned-memes-test
  
  This model is a fine-tuned version of [jayantapaul888/twitter-data-distilbert-base-uncased-sentiment-finetuned-memes](https://huggingface.co/jayantapaul888/twitter-data-distilbert-base-uncased-sentiment-finetuned-memes) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6985
  - Accuracy: 0.8218
  - Precision: 0.8225
  - Recall: 0.8218
  - F1: 0.8221
  
  ## 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: 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   | 294  | 0.4189          | 0.8124   | 0.8151    | 0.8124 | 0.8136 |
  | 0.4351        | 2.0   | 588  | 0.4057          | 0.8258   | 0.8275    | 0.8258 | 0.8263 |
  | 0.4351        | 3.0   | 882  | 0.4628          | 0.8220   | 0.8244    | 0.8220 | 0.8224 |
  | 0.2248        | 4.0   | 1176 | 0.5336          | 0.8250   | 0.8258    | 0.8250 | 0.8253 |
  | 0.2248        | 5.0   | 1470 | 0.6466          | 0.8208   | 0.8217    | 0.8208 | 0.8212 |
  | 0.1158        | 6.0   | 1764 | 0.6985          | 0.8218   | 0.8225    | 0.8218 | 0.8221 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0.dev0
  - Pytorch 1.11.0+cu102
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  