readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: finetuned-token-argumentative
    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. -->
  
  # finetuned-token-argumentative
  
  This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1573
  - Precision: 0.3777
  - Recall: 0.3919
  - F1: 0.3847
  - Accuracy: 0.9497
  
  ## 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 75   | 0.3241          | 0.1109    | 0.2178 | 0.1470 | 0.8488   |
  | No log        | 2.0   | 150  | 0.3145          | 0.1615    | 0.2462 | 0.1950 | 0.8606   |
  | No log        | 3.0   | 225  | 0.3035          | 0.1913    | 0.3258 | 0.2411 | 0.8590   |
  | No log        | 4.0   | 300  | 0.3080          | 0.2199    | 0.3220 | 0.2613 | 0.8612   |
  | No log        | 5.0   | 375  | 0.3038          | 0.2209    | 0.3277 | 0.2639 | 0.8630   |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.10.1+cu113
  - Datasets 1.18.0
  - Tokenizers 0.10.3
  