readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: prot_bert_classification_finetuned_training_script_trial
    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. -->
  
  # prot_bert_classification_finetuned_training_script_trial
  
  This model is a fine-tuned version of [nepp1d0/prot_bert-finetuned-smiles-bindingDB](https://huggingface.co/nepp1d0/prot_bert-finetuned-smiles-bindingDB) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6847
  - Accuracy: 0.86
  - F1: 0.9247
  - Precision: 1.0
  - Recall: 0.86
  
  ## 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-06
  - train_batch_size: 1
  - eval_batch_size: 1
  - seed: 3
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 4
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 5
  - num_epochs: 1
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
  | 0.6929        | 1.0   | 25   | 0.6847          | 0.86     | 0.9247 | 1.0       | 0.86   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  