readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  widget:
  - text: "Tachycardia is an increased heart rate for any reason. It can be a usual rise in heart rate caused by exercise or a stress response. Sinus tachycardia is considered a symptom, not a disease."
    example_title: "Tachycardia"
  - text: "Tuberclosis generally damages the lungs, but it can also impair other parts of the body such as brain and spine. Typical signs of active Tuberclosis include chronic cought with blood-containing mucus, fever, night sweats and weight loss. Tuberclosis damages the lungs whereas Malaria could detriment both kidneys by imparing the liver."
    example_title: "Tuberculosis"
  - text: "Cholera is a bacterial disease usually spread through contaminated water. A bacterium called Vibrio cholerae causes cholera infection. Symptoms of cholera infection can include: Diarrhea, Nausea, vomiting, Dehydration. Risk factors for cholera include: Poor sanitary conditions, Household exposure, Type O blood, Raw or undercooked shellfish."
    example_title: "Cholera"
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: electra-base-discriminator-new
    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. -->
  
  # electra-base-discriminator-new
  
  This model is a fine-tuned version of [bhadresh-savani/electra-base-discriminator-finetuned-conll03-english](https://huggingface.co/bhadresh-savani/electra-base-discriminator-finetuned-conll03-english) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6104
  - Precision: 0.4656
  - Recall: 0.6018
  - F1: 0.5250
  - Accuracy: 0.8111
  
  ## 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: 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: 30
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 180  | 1.1112          | 0.2541    | 0.3289 | 0.2867 | 0.7120   |
  | No log        | 2.0   | 360  | 0.7873          | 0.3562    | 0.4509 | 0.3980 | 0.7747   |
  | 1.1642        | 3.0   | 540  | 0.6838          | 0.4349    | 0.5468 | 0.4845 | 0.7990   |
  | 1.1642        | 4.0   | 720  | 0.6453          | 0.4419    | 0.5857 | 0.5037 | 0.8034   |
  | 1.1642        | 5.0   | 900  | 0.6104          | 0.4656    | 0.6018 | 0.5250 | 0.8111   |
  | 0.5738        | 6.0   | 1080 | 0.6151          | 0.4528    | 0.6206 | 0.5236 | 0.8089   |
  | 0.5738        | 7.0   | 1260 | 0.6519          | 0.4451    | 0.6427 | 0.5259 | 0.7998   |
  | 0.5738        | 8.0   | 1440 | 0.6443          | 0.4563    | 0.6543 | 0.5377 | 0.8061   |
  | 0.4186        | 9.0   | 1620 | 0.6536          | 0.4678    | 0.6553 | 0.5459 | 0.8044   |
  | 0.4186        | 10.0  | 1800 | 0.6564          | 0.4758    | 0.6626 | 0.5538 | 0.8046   |
  | 0.4186        | 11.0  | 1980 | 0.6795          | 0.4762    | 0.6560 | 0.5518 | 0.8042   |
  | 0.3287        | 12.0  | 2160 | 0.6729          | 0.4902    | 0.6563 | 0.5612 | 0.8125   |
  | 0.3287        | 13.0  | 2340 | 0.6692          | 0.5008    | 0.6545 | 0.5674 | 0.8137   |
  | 0.268         | 14.0  | 2520 | 0.7124          | 0.4743    | 0.6633 | 0.5531 | 0.8042   |
  | 0.268         | 15.0  | 2700 | 0.7118          | 0.4905    | 0.6653 | 0.5647 | 0.8089   |
  | 0.268         | 16.0  | 2880 | 0.7084          | 0.4933    | 0.6653 | 0.5665 | 0.8091   |
  | 0.2223        | 17.0  | 3060 | 0.7441          | 0.4740    | 0.6761 | 0.5573 | 0.8033   |
  | 0.2223        | 18.0  | 3240 | 0.7669          | 0.4842    | 0.6769 | 0.5645 | 0.8032   |
  | 0.2223        | 19.0  | 3420 | 0.7644          | 0.4966    | 0.6696 | 0.5703 | 0.8099   |
  | 0.1973        | 20.0  | 3600 | 0.7734          | 0.4830    | 0.6709 | 0.5616 | 0.8035   |
  | 0.1973        | 21.0  | 3780 | 0.7916          | 0.4874    | 0.6678 | 0.5635 | 0.8033   |
  | 0.1973        | 22.0  | 3960 | 0.7888          | 0.4990    | 0.6719 | 0.5727 | 0.8056   |
  | 0.1713        | 23.0  | 4140 | 0.7921          | 0.4942    | 0.6714 | 0.5693 | 0.8046   |
  | 0.1713        | 24.0  | 4320 | 0.8126          | 0.4850    | 0.6676 | 0.5619 | 0.8028   |
  | 0.1569        | 25.0  | 4500 | 0.8206          | 0.4908    | 0.6741 | 0.5680 | 0.8028   |
  | 0.1569        | 26.0  | 4680 | 0.8290          | 0.4919    | 0.6744 | 0.5689 | 0.8039   |
  | 0.1569        | 27.0  | 4860 | 0.8279          | 0.4924    | 0.6698 | 0.5676 | 0.8056   |
  | 0.1452        | 28.0  | 5040 | 0.8341          | 0.4852    | 0.6686 | 0.5623 | 0.8028   |
  | 0.145