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# recipe-roberta-upper-tIs

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: 0.7904

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.2671        | 1.0   | 1281  | 1.0554          |
| 1.0995        | 2.0   | 2562  | 0.9832          |
| 1.0339        | 3.0   | 3843  | 0.9389          |
| 0.9925        | 4.0   | 5124  | 0.9095          |
| 0.964         | 5.0   | 6405  | 0.8914          |
| 0.9426        | 6.0   | 7686  | 0.8708          |
| 0.9227        | 7.0   | 8967  | 0.8590          |
| 0.9082        | 8.0   | 10248 | 0.8448          |
| 0.8963        | 9.0   | 11529 | 0.8361          |
| 0.8847        | 10.0  | 12810 | 0.8249          |
| 0.8756        | 11.0  | 14091 | 0.8204          |
| 0.8672        | 12.0  | 15372 | 0.8105          |
| 0.8612        | 13.0  | 16653 | 0.8106          |
| 0.8561        | 14.0  | 17934 | 0.8041          |
| 0.8485        | 15.0  | 19215 | 0.7979          |
| 0.8452        | 16.0  | 20496 | 0.7910          |
| 0.8403        | 17.0  | 21777 | 0.7991          |
| 0.8389        | 18.0  | 23058 | 0.7928          |
| 0.8371        | 19.0  | 24339 | 0.7926          |
| 0.8341        | 20.0  | 25620 | 0.7904          |


### 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-upper-tIs", "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-upper-tIs
========================


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


* Loss: 0.7904


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