---
license: mit
base_model: facebook/esm2_t33_650M_UR50D
tags:
- generated_from_trainer
model-index:
- name: esm2_t33_650M_UR50D-finetuned-localization
  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_t33_650M_UR50D-finetuned-localization

This model is a fine-tuned version of [facebook/esm2_t33_650M_UR50D](https://huggingface.co/facebook/esm2_t33_650M_UR50D) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0689
- Rmse: 1.0339

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rmse   |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 226  | 1.2216          | 1.1052 |
| No log        | 2.0   | 452  | 1.7920          | 1.3387 |
| 1.7878        | 3.0   | 678  | 1.0784          | 1.0385 |
| 1.7878        | 4.0   | 904  | 1.4254          | 1.1939 |
| 1.2236        | 5.0   | 1130 | 1.5014          | 1.2253 |
| 1.2236        | 6.0   | 1356 | 1.3869          | 1.1777 |
| 0.6751        | 7.0   | 1582 | 0.9855          | 0.9927 |
| 0.6751        | 8.0   | 1808 | 1.1011          | 1.0493 |
| 0.2989        | 9.0   | 2034 | 1.3254          | 1.1512 |
| 0.2989        | 10.0  | 2260 | 1.1216          | 1.0590 |
| 0.2989        | 11.0  | 2486 | 1.1718          | 1.0825 |
| 0.1584        | 12.0  | 2712 | 1.0833          | 1.0408 |
| 0.1584        | 13.0  | 2938 | 1.0868          | 1.0425 |
| 0.0783        | 14.0  | 3164 | 1.0736          | 1.0362 |
| 0.0783        | 15.0  | 3390 | 1.0607          | 1.0299 |
| 0.0467        | 16.0  | 3616 | 1.0792          | 1.0388 |
| 0.0467        | 17.0  | 3842 | 1.0528          | 1.0261 |
| 0.0199        | 18.0  | 4068 | 1.0405          | 1.0201 |
| 0.0199        | 19.0  | 4294 | 1.0931          | 1.0455 |
| 0.0129        | 20.0  | 4520 | 1.0766          | 1.0376 |
| 0.0129        | 21.0  | 4746 | 1.0486          | 1.0240 |
| 0.0129        | 22.0  | 4972 | 1.0801          | 1.0393 |
| 0.0086        | 23.0  | 5198 | 1.0636          | 1.0313 |
| 0.0086        | 24.0  | 5424 | 1.0675          | 1.0332 |
| 0.0032        | 25.0  | 5650 | 1.0689          | 1.0339 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1
- Datasets 2.20.0
- Tokenizers 0.19.1