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# esm2_t6_8M_UR50D-crystallization-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: 0.4286
- F1: 0.6192

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 267  | 0.4463          | 0.4978 |
| 0.4639        | 2.0   | 534  | 0.4197          | 0.6117 |
| 0.4639        | 3.0   | 801  | 0.4122          | 0.6221 |
| 0.3671        | 4.0   | 1068 | 0.4069          | 0.6219 |
| 0.3671        | 5.0   | 1335 | 0.4059          | 0.6069 |
| 0.313         | 6.0   | 1602 | 0.4115          | 0.6238 |
| 0.313         | 7.0   | 1869 | 0.4154          | 0.6285 |
| 0.2764        | 8.0   | 2136 | 0.4200          | 0.6182 |
| 0.2764        | 9.0   | 2403 | 0.4288          | 0.5987 |
| 0.2463        | 10.0  | 2670 | 0.4286          | 0.6192 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["f1"], "model-index": [{"name": "esm2_t6_8M_UR50D-crystallization-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-crystallization-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: 0.4286
* F1: 0.6192


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: 1e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1
* Datasets 2.12.0
* Tokenizers 0.13.3
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: 1e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1
* Datasets 2.12.0
* Tokenizers 0.13.3