readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: roberta-large-finetuned-ADEs_model_2
    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-large-finetuned-ADEs_model_2
  
  This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2580
  - Precision: 0.5407
  - Recall: 0.6311
  - F1: 0.5824
  - Accuracy: 0.8897
  
  ## 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: 5e-07
  - 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 | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.7461        | 1.0   | 640  | 0.3393          | 0.4247    | 0.5095 | 0.4633 | 0.8648   |
  | 0.3632        | 2.0   | 1280 | 0.2822          | 0.4934    | 0.6035 | 0.5429 | 0.8819   |
  | 0.3102        | 3.0   | 1920 | 0.2663          | 0.5218    | 0.6112 | 0.5630 | 0.8879   |
  | 0.2806        | 4.0   | 2560 | 0.2604          | 0.5337    | 0.6311 | 0.5783 | 0.8890   |
  | 0.2772        | 5.0   | 3200 | 0.2580          | 0.5407    | 0.6311 | 0.5824 | 0.8897   |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  