readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: DistilBERT_FINAL_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. -->
  
  # DistilBERT_FINAL_ctxSentence_TRAIN_webDiscourse_TEST_NULL_second_train_set_null_False
  
  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: 2.0703
  - Precision: 0.9667
  - Recall: 0.0505
  - F1: 0.0961
  - Accuracy: 0.0766
  
  ## 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   | 0.5442          | 0.6667    | 0.1132 | 0.1935 | 0.75     |
  | No log        | 2.0   | 190  | 0.5316          | 0.5385    | 0.1321 | 0.2121 | 0.74     |
  | No log        | 3.0   | 285  | 0.5384          | 0.4615    | 0.2264 | 0.3038 | 0.725    |
  | No log        | 4.0   | 380  | 0.5503          | 0.4286    | 0.2264 | 0.2963 | 0.715    |
  | No log        | 5.0   | 475  | 0.5529          | 0.4286    | 0.2264 | 0.2963 | 0.715    |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.10.1+cu113
  - Datasets 1.18.0
  - Tokenizers 0.10.3
  