readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: DistilBERTFINAL_ctxSentence_TRAIN_webDiscourse_TEST_NULL_second_train_set_null_False
    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. -->
  
  # DistilBERTFINAL_ctxSentence_TRAIN_webDiscourse_TEST_NULL_second_train_set_null_False
  
  This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base](https://huggingface.co/cardiffnlp/twitter-roberta-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.2555
  - Precision: 1.0
  - Recall: 0.0200
  - F1: 0.0393
  - Accuracy: 0.0486
  
  ## 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: 1e-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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 95   | 0.5756          | nan       | 0.0    | nan    | 0.715    |
  | No log        | 2.0   | 190  | 0.5340          | 0.6429    | 0.1579 | 0.2535 | 0.735    |
  | No log        | 3.0   | 285  | 0.5298          | 0.5833    | 0.3684 | 0.4516 | 0.745    |
  | No log        | 4.0   | 380  | 0.5325          | 0.5789    | 0.3860 | 0.4632 | 0.745    |
  | No log        | 5.0   | 475  | 0.5452          | 0.4815    | 0.4561 | 0.4685 | 0.705    |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.10.1+cu113
  - Datasets 1.18.0
  - Tokenizers 0.10.3
  