---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: prot_bert_classification_finetuned
  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

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: 0.5675
- Accuracy: 0.7299
- F1: 0.7377
- Precision: 0.6995
- Recall: 0.7803

## 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: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4221        | 1.0   | 3332  | 0.6152          | 0.6615   | 0.6711 | 0.6367    | 0.7093 |
| 0.4133        | 2.0   | 6664  | 0.5840          | 0.6845   | 0.6718 | 0.6805    | 0.6634 |
| 0.4293        | 3.0   | 9996  | 0.5727          | 0.7116   | 0.7094 | 0.6961    | 0.7232 |
| 0.3098        | 4.0   | 13328 | 0.5636          | 0.7163   | 0.7220 | 0.6904    | 0.7566 |
| 0.3881        | 5.0   | 16660 | 0.5629          | 0.7265   | 0.7377 | 0.6918    | 0.7900 |
| 0.4943        | 6.0   | 19992 | 0.5675          | 0.7299   | 0.7377 | 0.6995    | 0.7803 |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1
