---
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: facebook/esm2_t30_150M_UR50D
metrics:
- accuracy
model-index:
- name: esm2_t130_150M-lora-classifier_2024-04-25_23-13-58
  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_t130_150M-lora-classifier_2024-04-25_23-13-58

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: 0.4754
- Accuracy: 0.8809

## 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: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.587         | 1.0   | 128  | 0.6443          | 0.5957   |
| 0.4373        | 2.0   | 256  | 0.6115          | 0.6699   |
| 0.3057        | 3.0   | 384  | 0.4991          | 0.7812   |
| 0.2758        | 4.0   | 512  | 0.4353          | 0.8242   |
| 0.4801        | 5.0   | 640  | 0.3155          | 0.8691   |
| 0.2161        | 6.0   | 768  | 0.3821          | 0.8301   |
| 0.178         | 7.0   | 896  | 0.2889          | 0.875    |
| 0.3202        | 8.0   | 1024 | 0.2716          | 0.8945   |
| 0.192         | 9.0   | 1152 | 0.3002          | 0.8848   |
| 0.0997        | 10.0  | 1280 | 0.3142          | 0.8828   |
| 0.0146        | 11.0  | 1408 | 0.3388          | 0.8965   |
| 0.0777        | 12.0  | 1536 | 0.4100          | 0.8711   |
| 0.0337        | 13.0  | 1664 | 0.3152          | 0.8848   |
| 0.4337        | 14.0  | 1792 | 0.4699          | 0.8848   |
| 0.2544        | 15.0  | 1920 | 0.3347          | 0.8867   |
| 0.0166        | 16.0  | 2048 | 0.4547          | 0.8770   |
| 0.0084        | 17.0  | 2176 | 0.3627          | 0.8867   |
| 0.3829        | 18.0  | 2304 | 0.3663          | 0.8887   |
| 0.096         | 19.0  | 2432 | 0.3994          | 0.8848   |
| 0.017         | 20.0  | 2560 | 0.4222          | 0.8867   |
| 0.0093        | 21.0  | 2688 | 0.4519          | 0.8906   |
| 0.0035        | 22.0  | 2816 | 0.4575          | 0.8828   |
| 0.0072        | 23.0  | 2944 | 0.4675          | 0.8828   |
| 0.0306        | 24.0  | 3072 | 0.4675          | 0.8867   |
| 0.1433        | 25.0  | 3200 | 0.4795          | 0.8828   |
| 0.0073        | 26.0  | 3328 | 0.4755          | 0.8789   |
| 0.3764        | 27.0  | 3456 | 0.4759          | 0.8809   |
| 0.02          | 28.0  | 3584 | 0.4723          | 0.8828   |
| 0.0061        | 29.0  | 3712 | 0.4736          | 0.8809   |
| 0.0042        | 30.0  | 3840 | 0.4754          | 0.8809   |


### Framework versions

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