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# Regression_electra_2

This model is a fine-tuned version of [google/electra-small-generator](https://huggingface.co/google/electra-small-generator) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 5.2032
- Mse: 5.2032
- Mae: 1.8032
- R2: -1.6847
- Accuracy: 0.0

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mse    | Mae    | R2      | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 1    | 4.3426          | 4.3426 | 1.8114 | -3.0746 | 0.1429   |
| No log        | 2.0   | 2    | 4.2398          | 4.2398 | 1.7830 | -2.9781 | 0.1429   |
| No log        | 3.0   | 3    | 4.1436          | 4.1436 | 1.7561 | -2.8878 | 0.1429   |
| No log        | 4.0   | 4    | 4.0529          | 4.0529 | 1.7305 | -2.8028 | 0.2857   |
| No log        | 5.0   | 5    | 3.9672          | 3.9672 | 1.7059 | -2.7223 | 0.2857   |
| No log        | 6.0   | 6    | 3.8864          | 3.8864 | 1.6825 | -2.6465 | 0.2857   |
| No log        | 7.0   | 7    | 3.8097          | 3.8097 | 1.6600 | -2.5746 | 0.2857   |
| No log        | 8.0   | 8    | 3.7376          | 3.7376 | 1.6386 | -2.5070 | 0.2857   |
| No log        | 9.0   | 9    | 3.6706          | 3.6706 | 1.6184 | -2.4441 | 0.2857   |
| No log        | 10.0  | 10   | 3.6084          | 3.6084 | 1.5995 | -2.3857 | 0.2857   |
| No log        | 11.0  | 11   | 3.5517          | 3.5517 | 1.5820 | -2.3325 | 0.2857   |
| No log        | 12.0  | 12   | 3.5000          | 3.5000 | 1.5659 | -2.2840 | 0.2857   |
| No log        | 13.0  | 13   | 3.4536          | 3.4536 | 1.5513 | -2.2405 | 0.2857   |
| No log        | 14.0  | 14   | 3.4127          | 3.4127 | 1.5382 | -2.2020 | 0.2857   |
| No log        | 15.0  | 15   | 3.3771          | 3.3771 | 1.5268 | -2.1687 | 0.2857   |
| No log        | 16.0  | 16   | 3.3474          | 3.3474 | 1.5171 | -2.1408 | 0.2857   |
| No log        | 17.0  | 17   | 3.3234          | 3.3234 | 1.5093 | -2.1183 | 0.2857   |
| No log        | 18.0  | 18   | 3.3052          | 3.3052 | 1.5034 | -2.1012 | 0.2857   |
| No log        | 19.0  | 19   | 3.2930          | 3.2930 | 1.4994 | -2.0898 | 0.2857   |
| No log        | 20.0  | 20   | 3.2869          | 3.2869 | 1.4974 | -2.0840 | 0.2857   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "Regression_electra_2", "results": []}]}
transformers pytorch tensorboard electra text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #electra #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

Regression\_electra\_2
======================


This model is a fine-tuned version of google/electra-small-generator on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 5.2032
* Mse: 5.2032
* Mae: 1.8032
* R2: -1.6847
* Accuracy: 0.0


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: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #electra #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #electra #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2