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# recipe-roberta-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: 0.8491

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.3552        | 1.0   | 1012  | 1.1292          |
| 1.1811        | 2.0   | 2024  | 1.0543          |
| 1.1095        | 3.0   | 3036  | 1.0122          |
| 1.0667        | 4.0   | 4048  | 0.9756          |
| 1.0345        | 5.0   | 5060  | 0.9478          |
| 1.0112        | 6.0   | 6072  | 0.9292          |
| 0.9922        | 7.0   | 7084  | 0.9137          |
| 0.9762        | 8.0   | 8096  | 0.9056          |
| 0.9627        | 9.0   | 9108  | 0.8977          |
| 0.9507        | 10.0  | 10120 | 0.8868          |
| 0.9411        | 11.0  | 11132 | 0.8823          |
| 0.9344        | 12.0  | 12144 | 0.8745          |
| 0.9261        | 13.0  | 13156 | 0.8688          |
| 0.9189        | 14.0  | 14168 | 0.8614          |
| 0.9133        | 15.0  | 15180 | 0.8609          |
| 0.9078        | 16.0  | 16192 | 0.8581          |
| 0.906         | 17.0  | 17204 | 0.8544          |
| 0.9015        | 18.0  | 18216 | 0.8537          |
| 0.8988        | 19.0  | 19228 | 0.8494          |
| 0.8975        | 20.0  | 20240 | 0.8491          |


### 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-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-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: 0.8491


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
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