readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: twitter-roberta-base-sentiment-latest-finetuned-FG-CONCAT_SENTENCE-H-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-CONCAT_SENTENCE-H-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: 3.6335
  - Accuracy: 0.5275
  - F1: 0.5198
  
  ## 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: 12
  - eval_batch_size: 12
  - 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   | 61   | 1.0568          | 0.4396   | 0.2684 |
  | No log        | 2.0   | 122  | 1.0518          | 0.4396   | 0.2684 |
  | No log        | 3.0   | 183  | 1.0584          | 0.4396   | 0.2684 |
  | No log        | 4.0   | 244  | 1.1720          | 0.3956   | 0.3223 |
  | No log        | 5.0   | 305  | 1.2473          | 0.5275   | 0.5196 |
  | No log        | 6.0   | 366  | 1.0789          | 0.5220   | 0.5301 |
  | No log        | 7.0   | 427  | 1.3556          | 0.5604   | 0.5426 |
  | No log        | 8.0   | 488  | 1.7314          | 0.5330   | 0.5158 |
  | 0.8045        | 9.0   | 549  | 2.2774          | 0.5330   | 0.5161 |
  | 0.8045        | 10.0  | 610  | 2.8362          | 0.4451   | 0.4512 |
  | 0.8045        | 11.0  | 671  | 2.9130          | 0.5275   | 0.4931 |
  | 0.8045        | 12.0  | 732  | 3.1023          | 0.5110   | 0.5010 |
  | 0.8045        | 13.0  | 793  | 3.2670          | 0.5385   | 0.5208 |
  | 0.8045        | 14.0  | 854  | 3.4151          | 0.4945   | 0.4856 |
  | 0.8045        | 15.0  | 915  | 3.7614          | 0.4615   | 0.4458 |
  | 0.8045        | 16.0  | 976  | 3.5224          | 0.5220   | 0.5122 |
  | 0.0535        | 17.0  | 1037 | 3.5196          | 0.5165   | 0.5102 |
  | 0.0535        | 18.0  | 1098 | 3.5791          | 0.5110   | 0.5039 |
  | 0.0535        | 19.0  | 1159 | 3.6220          | 0.5220   | 0.5137 |
  | 0.0535        | 20.0  | 1220 | 3.6335          | 0.5275   | 0.5198 |
  
  
  ### Framework versions
  
  - Transformers 4.16.2
  - Pytorch 1.9.1
  - Datasets 1.18.4
  - Tokenizers 0.11.6
  