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# recipe-roberta-i

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9919

## 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: 256
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.871         | 1.0   | 149  | 1.4670          |
| 1.528         | 2.0   | 298  | 1.3426          |
| 1.41          | 3.0   | 447  | 1.2636          |
| 1.3332        | 4.0   | 596  | 1.2029          |
| 1.2804        | 5.0   | 745  | 1.1646          |
| 1.2441        | 6.0   | 894  | 1.1351          |
| 1.21          | 7.0   | 1043 | 1.0898          |
| 1.182         | 8.0   | 1192 | 1.0725          |
| 1.1604        | 9.0   | 1341 | 1.0718          |
| 1.1402        | 10.0  | 1490 | 1.0529          |
| 1.1308        | 11.0  | 1639 | 1.0512          |
| 1.1191        | 12.0  | 1788 | 1.0245          |
| 1.0986        | 13.0  | 1937 | 1.0203          |
| 1.0919        | 14.0  | 2086 | 1.0158          |
| 1.084         | 15.0  | 2235 | 0.9930          |
| 1.0797        | 16.0  | 2384 | 0.9855          |
| 1.0697        | 17.0  | 2533 | 1.0061          |
| 1.0652        | 18.0  | 2682 | 0.9725          |
| 1.0658        | 19.0  | 2831 | 0.9861          |
| 1.0642        | 20.0  | 2980 | 0.9919          |


### Framework versions

- Transformers 4.19.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "recipe-roberta-i", "results": []}]}
transformers pytorch roberta fill-mask generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #fill-mask #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

recipe-roberta-i
================


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


* Loss: 0.9919


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: 256
* eval\_batch\_size: 256
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.19.0.dev0
* Pytorch 1.11.0+cu102
* Datasets 2.3.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 256
* eval\_batch\_size: 256
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.19.0.dev0
* Pytorch 1.11.0+cu102
* Datasets 2.3.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #roberta #fill-mask #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: 256
* eval\_batch\_size: 256
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.19.0.dev0
* Pytorch 1.11.0+cu102
* Datasets 2.3.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #roberta #fill-mask #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: 256
* eval\_batch\_size: 256
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.19.0.dev0
* Pytorch 1.11.0+cu102
* Datasets 2.3.2
* Tokenizers 0.12.1