---
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: facebook/esm2_t12_35M_UR50D
metrics:
- precision
- recall
- accuracy
model-index:
- name: esm2-t12-35M-lora-64-remote-homology-filtered
  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-t12-35M-lora-64-remote-homology-filtered

This model is a fine-tuned version of [facebook/esm2_t12_35M_UR50D](https://huggingface.co/facebook/esm2_t12_35M_UR50D) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5657
- Precision: 0.7166
- Recall: 0.6986
- F1-score: 0.7075
- Accuracy: 0.7141

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1-score | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:--------:|:--------:|
| 0.6191        | 1.0   | 7969  | 0.6185          | 0.6919    | 0.5824 | 0.6325   | 0.6650   |
| 0.5921        | 2.0   | 15938 | 0.5838          | 0.7201    | 0.6339 | 0.6742   | 0.6968   |
| 0.5874        | 3.0   | 23907 | 0.5751          | 0.7439    | 0.6104 | 0.6705   | 0.7032   |
| 0.5593        | 4.0   | 31876 | 0.5664          | 0.7210    | 0.6833 | 0.7016   | 0.7124   |
| 0.576         | 5.0   | 39845 | 0.5657          | 0.7166    | 0.6986 | 0.7075   | 0.7141   |


### Framework versions

- PEFT 0.11.1
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2