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# training_45k

This model is a fine-tuned version of [Sameen53/cv_bn_bestModel_1](https://huggingface.co/Sameen53/cv_bn_bestModel_1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: inf
- Wer: 0.1497

## 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-07
- 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: 500
- num_epochs: 7
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.2549        | 1.25  | 1500 | inf             | 0.1495 |
| 0.2482        | 2.51  | 3000 | inf             | 0.1496 |
| 0.2504        | 3.76  | 4500 | inf             | 0.1498 |
| 0.2479        | 5.02  | 6000 | inf             | 0.1495 |
| 0.2493        | 6.27  | 7500 | inf             | 0.1497 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "training_45k", "results": []}]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #endpoints_compatible #region-us 

training\_45k
=============


This model is a fine-tuned version of Sameen53/cv\_bn\_bestModel\_1 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: inf
* Wer: 0.1497


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-07
* 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: 500
* num\_epochs: 7
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.1+cu118
* Datasets 2.13.1
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-07
* 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: 500
* num\_epochs: 7
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.1+cu118
* Datasets 2.13.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-07
* 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: 500
* num\_epochs: 7
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.1+cu118
* Datasets 2.13.1
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-07
* 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: 500
* num\_epochs: 7
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.1+cu118
* Datasets 2.13.1
* Tokenizers 0.12.1