readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: roberta-base_fold_1_binary_v1
    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. -->
  
  # roberta-base_fold_1_binary_v1
  
  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.4984
  - F1: 0.8339
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 25
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | No log        | 1.0   | 288  | 0.3819          | 0.8117 |
  | 0.4108        | 2.0   | 576  | 0.3696          | 0.8281 |
  | 0.4108        | 3.0   | 864  | 0.4890          | 0.8343 |
  | 0.2261        | 4.0   | 1152 | 0.7605          | 0.8298 |
  | 0.2261        | 5.0   | 1440 | 0.7754          | 0.8307 |
  | 0.1404        | 6.0   | 1728 | 0.7650          | 0.8174 |
  | 0.0962        | 7.0   | 2016 | 0.8539          | 0.8315 |
  | 0.0962        | 8.0   | 2304 | 1.0770          | 0.8263 |
  | 0.0433        | 9.0   | 2592 | 1.1450          | 0.8292 |
  | 0.0433        | 10.0  | 2880 | 1.1700          | 0.8205 |
  | 0.0344        | 11.0  | 3168 | 1.2376          | 0.8241 |
  | 0.0344        | 12.0  | 3456 | 1.2688          | 0.8329 |
  | 0.0219        | 13.0  | 3744 | 1.3276          | 0.8283 |
  | 0.0123        | 14.0  | 4032 | 1.2930          | 0.8320 |
  | 0.0123        | 15.0  | 4320 | 1.4631          | 0.8266 |
  | 0.0177        | 16.0  | 4608 | 1.4326          | 0.8270 |
  | 0.0177        | 17.0  | 4896 | 1.4770          | 0.8334 |
  | 0.0053        | 18.0  | 5184 | 1.5972          | 0.8214 |
  | 0.0053        | 19.0  | 5472 | 1.5331          | 0.8327 |
  | 0.0045        | 20.0  | 5760 | 1.5487          | 0.8359 |
  | 0.0086        | 21.0  | 6048 | 1.4610          | 0.8315 |
  | 0.0086        | 22.0  | 6336 | 1.4685          | 0.8353 |
  | 0.0071        | 23.0  | 6624 | 1.4933          | 0.8358 |
  | 0.0071        | 24.0  | 6912 | 1.4898          | 0.8310 |
  | 0.0022        | 25.0  | 7200 | 1.4984          | 0.8339 |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  