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# hinglish-finetuned

This model is a fine-tuned version of [verloop/Hinglish-Bert](https://huggingface.co/verloop/Hinglish-Bert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0786

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.3784        | 1.0   | 80   | 3.0527          |
| 3.0398        | 2.0   | 160  | 2.8067          |
| 2.9133        | 3.0   | 240  | 2.7252          |
| 2.7872        | 4.0   | 320  | 2.5783          |
| 2.6205        | 5.0   | 400  | 2.5050          |
| 2.5979        | 6.0   | 480  | 2.4654          |
| 2.5655        | 7.0   | 560  | 2.4091          |
| 2.5412        | 8.0   | 640  | 2.3630          |
| 2.4479        | 9.0   | 720  | 2.3754          |
| 2.3724        | 10.0  | 800  | 2.2860          |
| 2.3842        | 11.0  | 880  | 2.2812          |
| 2.3411        | 12.0  | 960  | 2.2038          |
| 2.2617        | 13.0  | 1040 | 2.1887          |
| 2.3141        | 14.0  | 1120 | 2.1966          |
| 2.2115        | 15.0  | 1200 | 2.1248          |
| 2.2363        | 16.0  | 1280 | 2.1006          |
| 2.2191        | 17.0  | 1360 | 2.1248          |
| 2.1856        | 18.0  | 1440 | 2.0872          |
| 2.2009        | 19.0  | 1520 | 2.0299          |
| 2.2364        | 20.0  | 1600 | 2.0193          |
| 2.1785        | 21.0  | 1680 | 2.0227          |
| 2.1934        | 22.0  | 1760 | 2.0540          |
| 2.1479        | 23.0  | 1840 | 2.0381          |
| 2.0973        | 24.0  | 1920 | 1.9885          |
| 2.1376        | 25.0  | 2000 | 2.0142          |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "model-index": [{"name": "hinglish-finetuned", "results": []}]}
transformers pytorch tf tensorboard bert fill-mask generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tf #tensorboard #bert #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

hinglish-finetuned
==================


This model is a fine-tuned version of verloop/Hinglish-Bert on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 2.0786


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: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 25
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 25
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tf #tensorboard #bert #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 25
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.1.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tf #tensorboard #bert #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 25
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.1.0
* Tokenizers 0.12.1