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# Whisper Small English

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 en dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3107
- Wer: 12.0213

## 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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 40000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.1577        | 0.06  | 2500  | 0.4077          | 16.2349 |
| 0.2244        | 0.12  | 5000  | 0.3698          | 14.7325 |
| 0.3231        | 0.19  | 7500  | 0.3434          | 13.7448 |
| 0.2536        | 0.25  | 10000 | 0.3406          | 13.4981 |
| 0.2234        | 0.31  | 12500 | 0.3510          | 14.1304 |
| 0.1989        | 0.38  | 15000 | 0.3388          | 13.6394 |
| 0.2449        | 0.44  | 17500 | 0.3394          | 13.4293 |
| 0.2302        | 0.5   | 20000 | 0.3198          | 12.5020 |
| 0.213         | 0.56  | 22500 | 0.3167          | 12.4904 |
| 0.2395        | 0.62  | 25000 | 0.3145          | 12.7533 |
| 0.1152        | 0.69  | 27500 | 0.3181          | 12.6087 |
| 0.0901        | 1.01  | 30000 | 0.3134          | 12.3240 |
| 0.1595        | 1.07  | 32500 | 0.3107          | 12.0213 |
| 0.1249        | 1.13  | 35000 | 0.3131          | 12.0869 |
| 0.1404        | 1.2   | 37500 | 0.3117          | 12.4635 |
| 0.1812        | 1.26  | 40000 | 0.3104          | 12.1415 |


### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.11.1.dev0
- Tokenizers 0.13.2

{"language": ["en"], "license": "apache-2.0", "tags": ["whisper-event", "generated_from_trainer"], "datasets": ["mozilla-foundation/common_voice_11_0"], "metrics": ["wer"], "model-index": [{"name": "Whisper Small English", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "mozilla-foundation/common_voice_11_0 en", "type": "mozilla-foundation/common_voice_11_0", "config": "en", "split": "test", "args": "en"}, "metrics": [{"type": "wer", "value": 12.021334704238024, "name": "Wer"}]}]}]}
transformers pytorch tensorboard whisper automatic-speech-recognition whisper-event generated_from_trainer en dataset:mozilla-foundation/common_voice_11_0 license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #whisper-event #generated_from_trainer #en #dataset-mozilla-foundation/common_voice_11_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 

Whisper Small English
=====================


This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common\_voice\_11\_0 en dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3107
* Wer: 12.0213


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: 32
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* training\_steps: 40000
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.28.0.dev0
* Pytorch 2.0.0+cu117
* Datasets 2.11.1.dev0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 32
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* training\_steps: 40000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.0.dev0
* Pytorch 2.0.0+cu117
* Datasets 2.11.1.dev0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #whisper-event #generated_from_trainer #en #dataset-mozilla-foundation/common_voice_11_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 32
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* training\_steps: 40000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.0.dev0
* Pytorch 2.0.0+cu117
* Datasets 2.11.1.dev0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #whisper-event #generated_from_trainer #en #dataset-mozilla-foundation/common_voice_11_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 32
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* training\_steps: 40000
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.28.0.dev0
* Pytorch 2.0.0+cu117
* Datasets 2.11.1.dev0
* Tokenizers 0.13.2