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---
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
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