---
license: mit
base_model: facebook/esm2_t30_150M_UR50D
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: esm2_t30_150M_UR50D-finetuned-SO2F
  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. -->

# esm2_t30_150M_UR50D-finetuned-SO2F

This model is a fine-tuned version of [facebook/esm2_t30_150M_UR50D](https://huggingface.co/facebook/esm2_t30_150M_UR50D) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6608
- Accuracy: 0.7158
- Precision: 0.1682
- Recall: 0.5068
- F1: 0.2526
- Auc: 0.6223
- Mcc: 0.1585

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Auc    | Mcc    |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|:------:|
| No log        | 1.0   | 108  | 0.6768          | 0.6886   | 0.1465    | 0.4740 | 0.2238 | 0.5925 | 0.1175 |
| No log        | 2.0   | 216  | 0.6646          | 0.6935   | 0.1628    | 0.5397 | 0.2502 | 0.6247 | 0.1573 |
| No log        | 3.0   | 324  | 0.6608          | 0.7158   | 0.1682    | 0.5068 | 0.2526 | 0.6223 | 0.1585 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2