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# recipe-reg

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: 3.3717
- Rmse: 1.8362
- Mse: 3.3717
- Mae: 1.6145

## 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: 15

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Rmse   | Mse    | Mae    |
|:-------------:|:-----:|:------:|:---------------:|:------:|:------:|:------:|
| 3.3247        | 1.0   | 12809  | 3.3717          | 1.8362 | 3.3717 | 1.6145 |
| 3.3238        | 2.0   | 25618  | 3.3722          | 1.8363 | 3.3722 | 1.6145 |
| 3.3217        | 3.0   | 38427  | 3.3718          | 1.8362 | 3.3718 | 1.6145 |
| 3.3215        | 4.0   | 51236  | 3.3754          | 1.8372 | 3.3754 | 1.6145 |
| 3.3203        | 5.0   | 64045  | 3.3721          | 1.8363 | 3.3721 | 1.6145 |
| 3.3199        | 6.0   | 76854  | 3.3731          | 1.8366 | 3.3731 | 1.6145 |
| 3.319         | 7.0   | 89663  | 3.3731          | 1.8366 | 3.3731 | 1.6145 |
| 3.3188        | 8.0   | 102472 | 3.3717          | 1.8362 | 3.3717 | 1.6145 |


### 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-reg", "results": []}]}
transformers pytorch tensorboard roberta text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

recipe-reg
==========


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


* Loss: 3.3717
* Rmse: 1.8362
* Mse: 3.3717
* Mae: 1.6145


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: 15


### 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: 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: 15 ### 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 #tensorboard #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: 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: 15 ### 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 #tensorboard #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: 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: 15### Training results### Framework versions


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