readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: twitter-data-prosusai-finbert-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-prosusai-finbert-sentiment-finetuned-memes
  
  This model is a fine-tuned version of [ProsusAI/finbert](https://huggingface.co/ProsusAI/finbert) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5328
  - Accuracy: 0.9274
  - Precision: 0.9277
  - Recall: 0.9274
  - F1: 0.9275
  
  ## 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: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.3284        | 1.0   | 1783  | 0.2770          | 0.9140   | 0.9152    | 0.9140 | 0.9140 |
  | 0.2422        | 2.0   | 3566  | 0.2388          | 0.9282   | 0.9297    | 0.9282 | 0.9283 |
  | 0.207         | 3.0   | 5349  | 0.2291          | 0.9325   | 0.9337    | 0.9325 | 0.9326 |
  | 0.1829        | 4.0   | 7132  | 0.2298          | 0.9341   | 0.9347    | 0.9341 | 0.9340 |
  | 0.1665        | 5.0   | 8915  | 0.2493          | 0.9303   | 0.9309    | 0.9303 | 0.9304 |
  | 0.142         | 6.0   | 10698 | 0.2749          | 0.9306   | 0.9309    | 0.9306 | 0.9305 |
  | 0.1188        | 7.0   | 12481 | 0.2687          | 0.9279   | 0.9286    | 0.9279 | 0.9280 |
  | 0.1013        | 8.0   | 14264 | 0.2900          | 0.9270   | 0.9273    | 0.9270 | 0.9271 |
  | 0.0849        | 9.0   | 16047 | 0.3247          | 0.9261   | 0.9261    | 0.9261 | 0.9261 |
  | 0.0723        | 10.0  | 17830 | 0.3549          | 0.9259   | 0.9266    | 0.9259 | 0.9261 |
  | 0.057         | 11.0  | 19613 | 0.3706          | 0.9283   | 0.9288    | 0.9283 | 0.9284 |
  | 0.0496        | 12.0  | 21396 | 0.4070          | 0.9258   | 0.9266    | 0.9258 | 0.9260 |
  | 0.0423        | 13.0  | 23179 | 0.4361          | 0.9254   | 0.9262    | 0.9254 | 0.9256 |
  | 0.0355        | 14.0  | 24962 | 0.4602          | 0.9297   | 0.9305    | 0.9297 | 0.9298 |
  | 0.0291        | 15.0  | 26745 | 0.4859          | 0.9258   | 0.9259    | 0.9258 | 0.9258 |
  | 0.0248        | 16.0  | 28528 | 0.5024          | 0.9273   | 0.9274    | 0.9273 | 0.9273 |
  | 0.0219        | 17.0  | 30311 | 0.5093          | 0.9263   | 0.9264    | 0.9263 | 0.9263 |
  | 0.0191        | 18.0  | 32094 | 0.5244          | 0.9280   | 0.9288    | 0.9280 | 0.9282 |
  | 0.0171        | 19.0  | 33877 | 0.5290          | 0.9273   | 0.9276    | 0.9273 | 0.9274 |
  | 0.0172        | 20.0  | 35660 | 0.5328          | 0.9274   | 0.9277    | 0.9274 | 0.9275 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0.dev0
  - Pytorch 1.11.0+cu102
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  