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# whisper-base-voice-commands

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2549
- Wer: 0.0

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.1469        | 2.55  | 250  | 0.2371          | 0.0825 |
| 0.1369        | 5.1   | 500  | 0.2457          | 0.0    |
| 0.131         | 7.65  | 750  | 0.2549          | 0.0    |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "whisper-base-voice-commands", "results": []}]}
transformers pytorch tensorboard whisper automatic-speech-recognition generated_from_trainer endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #generated_from_trainer #endpoints_compatible #region-us 

whisper-base-voice-commands
===========================


This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2549
* Wer: 0.0


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: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.32.0.dev0
* Pytorch 2.0.1+cu118
* Datasets 2.14.4
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.32.0.dev0
* Pytorch 2.0.1+cu118
* Datasets 2.14.4
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #generated_from_trainer #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.32.0.dev0
* Pytorch 2.0.1+cu118
* Datasets 2.14.4
* Tokenizers 0.13.3