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# cv_bn_bestModel_1

This model is a fine-tuned version of [Sameen53/facebook_large_CV_bn3](https://huggingface.co/Sameen53/facebook_large_CV_bn3) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1780
- Wer: 0.2315

## 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: 5e-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.1588        | 1.3   | 1500 | 0.2097          | 0.2315 |
| 0.2126        | 2.6   | 3000 | 0.1941          | 0.2310 |
| 0.2242        | 3.9   | 4500 | 0.1834          | 0.2307 |
| 0.2303        | 5.2   | 6000 | 0.1780          | 0.2315 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "datasets": ["common_voice"], "model-index": [{"name": "cv_bn_bestModel_1", "results": []}]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer dataset:common_voice endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #endpoints_compatible #region-us 

cv\_bn\_bestModel\_1
====================


This model is a fine-tuned version of Sameen53/facebook\_large\_CV\_bn3 on the common\_voice dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1780
* Wer: 0.2315


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: 5e-06
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 200
* num\_epochs: 6
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.20.1
* Pytorch 1.11.0
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-06
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 200
* num\_epochs: 6
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.11.0
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-06
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 200
* num\_epochs: 6
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.11.0
* Datasets 2.1.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-06
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 200
* num\_epochs: 6
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.20.1
* Pytorch 1.11.0
* Datasets 2.1.0
* Tokenizers 0.12.1