
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# recipe-distilbert-s

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0321

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.8594        | 1.0   | 844   | 1.4751          |
| 1.4763        | 2.0   | 1688  | 1.3282          |
| 1.3664        | 3.0   | 2532  | 1.2553          |
| 1.2975        | 4.0   | 3376  | 1.2093          |
| 1.2543        | 5.0   | 4220  | 1.1667          |
| 1.2189        | 6.0   | 5064  | 1.1472          |
| 1.1944        | 7.0   | 5908  | 1.1251          |
| 1.1737        | 8.0   | 6752  | 1.1018          |
| 1.1549        | 9.0   | 7596  | 1.0950          |
| 1.1387        | 10.0  | 8440  | 1.0796          |
| 1.1295        | 11.0  | 9284  | 1.0713          |
| 1.1166        | 12.0  | 10128 | 1.0639          |
| 1.1078        | 13.0  | 10972 | 1.0485          |
| 1.099         | 14.0  | 11816 | 1.0431          |
| 1.0951        | 15.0  | 12660 | 1.0425          |
| 1.0874        | 16.0  | 13504 | 1.0323          |
| 1.0828        | 17.0  | 14348 | 1.0368          |
| 1.0802        | 18.0  | 15192 | 1.0339          |
| 1.0798        | 19.0  | 16036 | 1.0247          |
| 1.0758        | 20.0  | 16880 | 1.0321          |


### Framework versions

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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "recipe-distilbert-s", "results": []}]}
transformers pytorch distilbert fill-mask generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

recipe-distilbert-s
===================


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


* Loss: 1.0321


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 #distilbert #fill-mask #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: 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 #distilbert #fill-mask #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: 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