readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: finbert-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. -->
  
  # finbert-finetuned-FG-SINGLE_SENTENCE-NEWS
  
  This model is a fine-tuned version of [ProsusAI/finbert](https://huggingface.co/ProsusAI/finbert) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.2997
  - Accuracy: 0.6414
  - F1: 0.6295
  
  ## 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  | 0.9371          | 0.5699   | 0.4333 |
  | 0.9282        | 2.0   | 642  | 0.9135          | 0.5930   | 0.5447 |
  | 0.9282        | 3.0   | 963  | 0.9900          | 0.6033   | 0.5823 |
  | 0.6743        | 4.0   | 1284 | 1.0802          | 0.6142   | 0.6065 |
  | 0.3134        | 5.0   | 1605 | 1.5156          | 0.6183   | 0.5971 |
  | 0.3134        | 6.0   | 1926 | 1.3695          | 0.6319   | 0.6183 |
  | 0.1709        | 7.0   | 2247 | 1.8746          | 0.6462   | 0.6267 |
  | 0.1112        | 8.0   | 2568 | 2.0880          | 0.6176   | 0.6155 |
  | 0.1112        | 9.0   | 2889 | 2.3953          | 0.6190   | 0.6087 |
  | 0.0811        | 10.0  | 3210 | 2.3792          | 0.6339   | 0.6225 |
  | 0.0608        | 11.0  | 3531 | 2.3783          | 0.6360   | 0.6282 |
  | 0.0608        | 12.0  | 3852 | 2.5982          | 0.6544   | 0.6351 |
  | 0.039         | 13.0  | 4173 | 2.7687          | 0.6346   | 0.6305 |
  | 0.039         | 14.0  | 4494 | 2.8980          | 0.6414   | 0.6299 |
  | 0.0206        | 15.0  | 4815 | 3.0858          | 0.6319   | 0.6253 |
  | 0.0168        | 16.0  | 5136 | 3.2408          | 0.6244   | 0.6170 |
  | 0.0168        | 17.0  | 5457 | 3.1809          | 0.6435   | 0.6293 |
  | 0.0123        | 18.0  | 5778 | 3.2629          | 0.6449   | 0.6324 |
  | 0.0055        | 19.0  | 6099 | 3.2866          | 0.6449   | 0.6308 |
  | 0.0055        | 20.0  | 6420 | 3.2997          | 0.6414   | 0.6295 |
  
  
  ### Framework versions
  
  - Transformers 4.16.2
  - Pytorch 1.9.1
  - Datasets 1.18.4
  - Tokenizers 0.11.6
  