---
base_model: facebook/esm2_t6_8M_UR50D
library_name: peft
license: mit
metrics:
- accuracy
- precision
- recall
- f1
tags:
- generated_from_trainer
model-index:
- name: esm2_t12_35M-lora-binding-sites_2024-07-02_09-26-54
  results: []
---

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# esm2_t6_8M-lora-binding-sites_2024-07-02_09-26-54

This model is a fine-tuned version of [facebook/esm2_t6_8M_UR50D](https://huggingface.co/facebook/esm2_t6_8M_UR50D) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3706
- Accuracy: 0.8880
- Precision: 0.1563
- Recall: 0.7878
- F1: 0.2608
- Auc: 0.8392
- Mcc: 0.3192

## 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: 0.0005701568055793089
- train_batch_size: 12
- eval_batch_size: 12
- seed: 8893
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     | Auc    | Mcc    |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|:------:|
| 0.2569        | 1.0   | 14485 | 0.3706          | 0.8880   | 0.1563    | 0.7878 | 0.2608 | 0.8392 | 0.3192 |


### Framework versions

- PEFT 0.11.1
- Transformers 4.40.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1