readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: ProtBert-finetuned-proteinBindingDB
    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. -->
  
  # ProtBert-finetuned-proteinBindingDB
  
  This model is a fine-tuned version of [Rostlab/prot_bert](https://huggingface.co/Rostlab/prot_bert) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5764
  - Accuracy: 0.885
  - F1: 0.8459
  - Precision: 0.8255
  - Recall: 0.885
  
  ## 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: 1
  - eval_batch_size: 1
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
  | 0.8056        | 1.0   | 5000  | 1.5153          | 0.745    | 0.6391 | 0.5606    | 0.745  |
  | 0.7873        | 2.0   | 10000 | 0.5976          | 0.865    | 0.8267 | 0.8063    | 0.865  |
  | 0.7427        | 3.0   | 15000 | 0.6316          | 0.875    | 0.8364 | 0.8176    | 0.875  |
  | 1.0022        | 4.0   | 20000 | 0.6766          | 0.85     | 0.8112 | 0.7951    | 0.85   |
  | 0.7379        | 5.0   | 25000 | 0.6181          | 0.865    | 0.8267 | 0.8063    | 0.865  |
  | 0.6987        | 6.0   | 30000 | 0.7094          | 0.87     | 0.8336 | 0.82      | 0.87   |
  | 0.6984        | 7.0   | 35000 | 0.5377          | 0.885    | 0.8471 | 0.8290    | 0.885  |
  | 0.6657        | 8.0   | 40000 | 0.6278          | 0.875    | 0.8373 | 0.8213    | 0.875  |
  | 0.6695        | 9.0   | 45000 | 0.6323          | 0.88     | 0.8421 | 0.8240    | 0.88   |
  | 0.6352        | 10.0  | 50000 | 0.5764          | 0.885    | 0.8459 | 0.8255    | 0.885  |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  