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# esm2_t6_8M_UR50D-finetuned-localization

This model is a fine-tuned version of [facebook/esm2_t6_8M_UR50D](https://huggingface.co/facebook/esm2_t6_8M_UR50D) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0064
- R Squared: 0.882

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | R Squared |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| 0.0023        | 1.0   | 1504 | 0.0075          | 0.862     |
| 0.0018        | 2.0   | 3008 | 0.0064          | 0.882     |
| 0.0008        | 3.0   | 4512 | 0.0064          | 0.882     |


### Framework versions

- Transformers 4.28.1
- Pytorch 1.12.1
- Datasets 2.11.0
- Tokenizers 0.11.0

{"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "esm2_t6_8M_UR50D-finetuned-localization", "results": []}]}
transformers pytorch esm text-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #esm #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

esm2\_t6\_8M\_UR50D-finetuned-localization
==========================================


This model is a fine-tuned version of facebook/esm2\_t6\_8M\_UR50D on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0064
* R Squared: 0.882


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: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 1.12.1
* Datasets 2.11.0
* Tokenizers 0.11.0



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 1.12.1
* Datasets 2.11.0
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #esm #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 1.12.1
* Datasets 2.11.0
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #esm #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3### Training results### Framework versions


* Transformers 4.28.1
* Pytorch 1.12.1
* Datasets 2.11.0
* Tokenizers 0.11.0