---
license: mit
base_model: facebook/esm2_t12_35M_UR50D
tags:
- generated_from_trainer
metrics:
- spearmanr
model-index:
- name: esm2_t12_35M_UR50D-finetuned-rep7868aav2-v0
  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_UR50D-finetuned-rep7868aav2-v0

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: 0.0513
- Spearmanr: 0.7389

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Spearmanr |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|
| 0.118         | 1.0   | 1180  | 0.1154          | 0.3185    |
| 0.1156        | 2.0   | 2360  | 0.1109          | 0.3383    |
| 0.1143        | 3.0   | 3540  | 0.1162          | 0.3194    |
| 0.1192        | 4.0   | 4720  | 0.1111          | 0.2974    |
| 0.1147        | 5.0   | 5900  | 0.1125          | 0.4043    |
| 0.1196        | 6.0   | 7080  | 0.1116          | 0.1580    |
| 0.1171        | 7.0   | 8260  | 0.1114          | 0.2923    |
| 0.1177        | 8.0   | 9440  | 0.1106          | 0.3592    |
| 0.1126        | 9.0   | 10620 | 0.1105          | 0.3724    |
| 0.1152        | 10.0  | 11800 | 0.1135          | 0.4947    |
| 0.1159        | 11.0  | 12980 | 0.1082          | 0.5113    |
| 0.0953        | 12.0  | 14160 | 0.0820          | 0.6096    |
| 0.0798        | 13.0  | 15340 | 0.0688          | 0.6442    |
| 0.074         | 14.0  | 16520 | 0.0710          | 0.6738    |
| 0.0704        | 15.0  | 17700 | 0.0816          | 0.6736    |
| 0.0678        | 16.0  | 18880 | 0.0596          | 0.7142    |
| 0.0599        | 17.0  | 20060 | 0.0689          | 0.7187    |
| 0.0568        | 18.0  | 21240 | 0.0566          | 0.7308    |
| 0.0534        | 19.0  | 22420 | 0.0518          | 0.7340    |
| 0.0522        | 20.0  | 23600 | 0.0513          | 0.7389    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1