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# recipe-gauss-2

This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4204
- Rmse: 0.6484
- Mse: 0.4204
- Mae: 0.4557

## 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: 5e-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 | Rmse   | Mse    | Mae    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|
| 0.4002        | 1.0   | 3029  | 0.4228          | 0.6502 | 0.4228 | 0.4485 |
| 0.3986        | 2.0   | 6058  | 0.4200          | 0.6481 | 0.4200 | 0.4566 |
| 0.3985        | 3.0   | 9087  | 0.4217          | 0.6494 | 0.4217 | 0.4515 |
| 0.3977        | 4.0   | 12116 | 0.4212          | 0.6490 | 0.4212 | 0.4528 |
| 0.397         | 5.0   | 15145 | 0.4251          | 0.6520 | 0.4251 | 0.4461 |
| 0.397         | 6.0   | 18174 | 0.4203          | 0.6483 | 0.4203 | 0.4665 |
| 0.3968        | 7.0   | 21203 | 0.4211          | 0.6489 | 0.4211 | 0.4533 |
| 0.3964        | 8.0   | 24232 | 0.4208          | 0.6487 | 0.4208 | 0.4543 |
| 0.3963        | 9.0   | 27261 | 0.4199          | 0.6480 | 0.4199 | 0.4604 |
| 0.3961        | 10.0  | 30290 | 0.4204          | 0.6484 | 0.4204 | 0.4557 |


### Framework versions

- Transformers 4.19.0.dev0
- Pytorch 1.9.0+cu111
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "recipe-gauss-2", "results": []}]}
transformers pytorch roberta text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

recipe-gauss-2
==============


This model is a fine-tuned version of distilroberta-base on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.4204
* Rmse: 0.6484
* Mse: 0.4204
* Mae: 0.4557


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: 5e-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 4.19.0.dev0
* Pytorch 1.9.0+cu111
* Datasets 2.4.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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 4.19.0.dev0
* Pytorch 1.9.0+cu111
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #roberta #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: 5e-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 4.19.0.dev0
* Pytorch 1.9.0+cu111
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #roberta #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: 5e-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 4.19.0.dev0
* Pytorch 1.9.0+cu111
* Datasets 2.4.0
* Tokenizers 0.12.1