---
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
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# 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