---
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: facebook/esm2_t12_35M_UR50D
metrics:
- accuracy
model-index:
- name: esm2_t12_35M-lora-binding-sites_2024-04-25_17-02-01
  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-binding-sites_2024-04-25_17-02-01

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: 0.3783
- Accuracy: 0.8613

## 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: 64
- eval_batch_size: 64
- seed: 8893
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6443        | 1.0   | 24   | 0.6716          | 0.5977   |
| 0.6838        | 2.0   | 48   | 0.6690          | 0.5977   |
| 0.5906        | 3.0   | 72   | 0.6440          | 0.5977   |
| 0.585         | 4.0   | 96   | 0.5897          | 0.7012   |
| 0.6142        | 5.0   | 120  | 0.5522          | 0.6992   |
| 0.61          | 6.0   | 144  | 0.5307          | 0.7148   |
| 0.5131        | 7.0   | 168  | 0.5134          | 0.75     |
| 0.365         | 8.0   | 192  | 0.4437          | 0.8105   |
| 0.4282        | 9.0   | 216  | 0.4010          | 0.8379   |
| 0.3102        | 10.0  | 240  | 0.3643          | 0.8516   |
| 0.41          | 11.0  | 264  | 0.3624          | 0.8652   |
| 0.317         | 12.0  | 288  | 0.3877          | 0.8145   |
| 0.2332        | 13.0  | 312  | 0.3383          | 0.8672   |
| 0.2698        | 14.0  | 336  | 0.3389          | 0.8672   |
| 0.1326        | 15.0  | 360  | 0.3548          | 0.8535   |
| 0.1187        | 16.0  | 384  | 0.3313          | 0.8770   |
| 0.1597        | 17.0  | 408  | 0.3447          | 0.8652   |
| 0.1886        | 18.0  | 432  | 0.3543          | 0.8672   |
| 0.1883        | 19.0  | 456  | 0.3396          | 0.875    |
| 0.1156        | 20.0  | 480  | 0.3510          | 0.8652   |
| 0.2604        | 21.0  | 504  | 0.3529          | 0.875    |
| 0.1104        | 22.0  | 528  | 0.3654          | 0.8711   |
| 0.1723        | 23.0  | 552  | 0.3631          | 0.8691   |
| 0.1516        | 24.0  | 576  | 0.3719          | 0.8633   |
| 0.0731        | 25.0  | 600  | 0.3745          | 0.8672   |
| 0.1381        | 26.0  | 624  | 0.3765          | 0.8691   |
| 0.291         | 27.0  | 648  | 0.3760          | 0.8613   |
| 0.0924        | 28.0  | 672  | 0.3789          | 0.8633   |
| 0.2029        | 29.0  | 696  | 0.3783          | 0.8594   |
| 0.242         | 30.0  | 720  | 0.3783          | 0.8613   |


### Framework versions

- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.2.1
- Datasets 2.16.1
- Tokenizers 0.15.2