readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  - accuracy
  - recall
  - precision
  model-index:
  - name: roberta_reman
    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_reman
  
  This model is a fine-tuned version of [ibm/ColD-Fusion](https://huggingface.co/ibm/ColD-Fusion) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4272
  - F1: 0.7004
  - Roc Auc: 0.7862
  - Accuracy: 0.4330
  - Recall: 0.6831
  - Precision: 0.7185
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy | Recall | Precision |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|:------:|:---------:|
  | No log        | 1.0   | 113  | 0.4673          | 0.5668 | 0.6955  | 0.2990   | 0.4930 | 0.6667    |
  | No log        | 2.0   | 226  | 0.4187          | 0.6397 | 0.7403  | 0.3918   | 0.5563 | 0.7524    |
  | No log        | 3.0   | 339  | 0.4272          | 0.7004 | 0.7862  | 0.4330   | 0.6831 | 0.7185    |
  | No log        | 4.0   | 452  | 0.4191          | 0.6566 | 0.7539  | 0.3918   | 0.6127 | 0.7073    |
  | 0.3529        | 5.0   | 565  | 0.4246          | 0.6788 | 0.7706  | 0.4124   | 0.6549 | 0.7045    |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1+rocm5.2
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  