---
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: 1.1216
- Rmse: 1.0591

## 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  | 1.2900          | 1.1358 |
| No log        | 2.0   | 452  | 1.3499          | 1.1618 |
| 1.1023        | 3.0   | 678  | 1.0602          | 1.0297 |
| 1.1023        | 4.0   | 904  | 1.2692          | 1.1266 |
| 0.4485        | 5.0   | 1130 | 1.3467          | 1.1605 |
| 0.4485        | 6.0   | 1356 | 1.2897          | 1.1356 |
| 0.2574        | 7.0   | 1582 | 1.1185          | 1.0576 |
| 0.2574        | 8.0   | 1808 | 1.2362          | 1.1119 |
| 0.1358        | 9.0   | 2034 | 1.1828          | 1.0876 |
| 0.1358        | 10.0  | 2260 | 1.1376          | 1.0666 |
| 0.1358        | 11.0  | 2486 | 1.3182          | 1.1481 |
| 0.1139        | 12.0  | 2712 | 1.1802          | 1.0864 |
| 0.1139        | 13.0  | 2938 | 1.1709          | 1.0821 |
| 0.0587        | 14.0  | 3164 | 1.1167          | 1.0568 |
| 0.0587        | 15.0  | 3390 | 1.0711          | 1.0350 |
| 0.0369        | 16.0  | 3616 | 1.1464          | 1.0707 |
| 0.0369        | 17.0  | 3842 | 1.1536          | 1.0741 |
| 0.0183        | 18.0  | 4068 | 1.1041          | 1.0507 |
| 0.0183        | 19.0  | 4294 | 1.1113          | 1.0542 |
| 0.0106        | 20.0  | 4520 | 1.1453          | 1.0702 |
| 0.0106        | 21.0  | 4746 | 1.1076          | 1.0524 |
| 0.0106        | 22.0  | 4972 | 1.1358          | 1.0657 |
| 0.0053        | 23.0  | 5198 | 1.1298          | 1.0629 |
| 0.0053        | 24.0  | 5424 | 1.1182          | 1.0575 |
| 0.0007        | 25.0  | 5650 | 1.1216          | 1.0591 |


### Framework versions

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