---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: prot_bert_classification_finetuned_karolina_es_20e
  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_karolina_es_20e

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: 0.6763
- Accuracy: 0.92
- F1: 0.9583
- Precision: 1.0
- Recall: 0.92

## 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: 64
- eval_batch_size: 64
- seed: 3
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 2    | 0.7084          | 0.02     | 0.0392 | 1.0       | 0.02   |
| No log        | 2.0   | 4    | 0.7082          | 0.02     | 0.0392 | 1.0       | 0.02   |
| No log        | 3.0   | 6    | 0.7078          | 0.04     | 0.0769 | 1.0       | 0.04   |
| No log        | 4.0   | 8    | 0.7072          | 0.04     | 0.0769 | 1.0       | 0.04   |
| No log        | 5.0   | 10   | 0.7065          | 0.04     | 0.0769 | 1.0       | 0.04   |
| No log        | 6.0   | 12   | 0.7055          | 0.04     | 0.0769 | 1.0       | 0.04   |
| No log        | 7.0   | 14   | 0.7044          | 0.04     | 0.0769 | 1.0       | 0.04   |
| No log        | 8.0   | 16   | 0.7031          | 0.06     | 0.1132 | 1.0       | 0.06   |
| No log        | 9.0   | 18   | 0.7017          | 0.12     | 0.2143 | 1.0       | 0.12   |
| No log        | 10.0  | 20   | 0.6999          | 0.2      | 0.3333 | 1.0       | 0.2    |
| No log        | 11.0  | 22   | 0.6981          | 0.22     | 0.3607 | 1.0       | 0.22   |
| No log        | 12.0  | 24   | 0.6962          | 0.22     | 0.3607 | 1.0       | 0.22   |
| No log        | 13.0  | 26   | 0.6941          | 0.24     | 0.3871 | 1.0       | 0.24   |
| No log        | 14.0  | 28   | 0.6917          | 0.44     | 0.6111 | 1.0       | 0.44   |
| No log        | 15.0  | 30   | 0.6893          | 0.58     | 0.7342 | 1.0       | 0.58   |
| No log        | 16.0  | 32   | 0.6869          | 0.76     | 0.8636 | 1.0       | 0.76   |
| No log        | 17.0  | 34   | 0.6842          | 0.88     | 0.9362 | 1.0       | 0.88   |
| No log        | 18.0  | 36   | 0.6816          | 0.9      | 0.9474 | 1.0       | 0.9    |
| No log        | 19.0  | 38   | 0.6789          | 0.92     | 0.9583 | 1.0       | 0.92   |
| No log        | 20.0  | 40   | 0.6763          | 0.92     | 0.9583 | 1.0       | 0.92   |


### Framework versions

- Transformers 4.23.1
- Pytorch 1.11.0
- Datasets 2.6.1
- Tokenizers 0.13.1