readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: twitter-roberta-base-sentiment-latest-finetuned-FG-SINGLE_SENTENCE-NEWS
    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-roberta-base-sentiment-latest-finetuned-FG-SINGLE_SENTENCE-NEWS
  
  This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.2822
  - Accuracy: 0.6305
  - F1: 0.6250
  
  ## 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: 6e-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: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | No log        | 1.0   | 321  | 0.9646          | 0.5624   | 0.4048 |
  | 0.9537        | 2.0   | 642  | 0.9474          | 0.5644   | 0.4176 |
  | 0.9537        | 3.0   | 963  | 0.9008          | 0.5903   | 0.5240 |
  | 0.858         | 4.0   | 1284 | 0.9939          | 0.5999   | 0.5846 |
  | 0.5908        | 5.0   | 1605 | 1.0947          | 0.6108   | 0.6026 |
  | 0.5908        | 6.0   | 1926 | 1.2507          | 0.5740   | 0.5823 |
  | 0.3676        | 7.0   | 2247 | 1.4717          | 0.6128   | 0.6017 |
  | 0.2246        | 8.0   | 2568 | 1.6726          | 0.5965   | 0.6003 |
  | 0.2246        | 9.0   | 2889 | 1.8041          | 0.6380   | 0.6298 |
  | 0.1468        | 10.0  | 3210 | 1.9796          | 0.6053   | 0.6026 |
  | 0.1161        | 11.0  | 3531 | 2.0988          | 0.6237   | 0.6202 |
  | 0.1161        | 12.0  | 3852 | 2.4171          | 0.5944   | 0.5989 |
  | 0.0916        | 13.0  | 4173 | 2.3326          | 0.6374   | 0.6288 |
  | 0.0916        | 14.0  | 4494 | 2.5472          | 0.6360   | 0.6245 |
  | 0.0661        | 15.0  | 4815 | 2.9127          | 0.6176   | 0.6187 |
  | 0.0454        | 16.0  | 5136 | 2.9133          | 0.6326   | 0.6276 |
  | 0.0454        | 17.0  | 5457 | 3.1299          | 0.6210   | 0.6162 |
  | 0.0337        | 18.0  | 5778 | 3.1828          | 0.6224   | 0.6188 |
  | 0.0223        | 19.0  | 6099 | 3.2655          | 0.6299   | 0.6223 |
  | 0.0223        | 20.0  | 6420 | 3.2822          | 0.6305   | 0.6250 |
  
  
  ### Framework versions
  
  - Transformers 4.16.2
  - Pytorch 1.9.1
  - Datasets 1.18.4
  - Tokenizers 0.11.6
  