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# Whisper tiny ID - Augmented

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the mozilla-foundation/common_voice_12_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2874
- Wer: 14.4271

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- 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: 100
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.6729        | 0.77  | 200  | 0.4170          | 21.8473 |
| 0.5012        | 1.54  | 400  | 0.3465          | 18.2560 |
| 0.3832        | 2.31  | 600  | 0.3097          | 16.0971 |
| 0.2853        | 3.07  | 800  | 0.2970          | 14.3180 |
| 0.2416        | 3.84  | 1000 | 0.2874          | 14.4271 |


### Framework versions

- Transformers 4.29.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2

{"language": ["id"], "license": "apache-2.0", "tags": ["whisper-event", "generated_from_trainer"], "datasets": ["mozilla-foundation/common_voice_12_0"], "metrics": ["wer"], "model-index": [{"name": "Whisper tiny ID - Augmented", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "mozilla-foundation/common_voice_12_0", "type": "mozilla-foundation/common_voice_12_0", "config": "id", "split": "test", "args": "id"}, "metrics": [{"type": "wer", "value": 14.42705294401177, "name": "Wer"}, {"type": "wer", "value": 14.42705294401177, "name": "WER"}]}]}]}
transformers pytorch tensorboard whisper automatic-speech-recognition whisper-event generated_from_trainer id dataset:mozilla-foundation/common_voice_12_0 license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #whisper-event #generated_from_trainer #id #dataset-mozilla-foundation/common_voice_12_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 

Whisper tiny ID - Augmented
===========================


This model is a fine-tuned version of openai/whisper-tiny on the mozilla-foundation/common\_voice\_12\_0 dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2874
* Wer: 14.4271


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: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 16
* 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: 100
* training\_steps: 1000
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.29.0.dev0
* Pytorch 2.0.0+cu117
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 16
* 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: 100
* training\_steps: 1000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.0.dev0
* Pytorch 2.0.0+cu117
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #whisper-event #generated_from_trainer #id #dataset-mozilla-foundation/common_voice_12_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: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 16
* 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: 100
* training\_steps: 1000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.0.dev0
* Pytorch 2.0.0+cu117
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #whisper-event #generated_from_trainer #id #dataset-mozilla-foundation/common_voice_12_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: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 16
* 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: 100
* training\_steps: 1000
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.29.0.dev0
* Pytorch 2.0.0+cu117
* Datasets 2.10.1
* Tokenizers 0.13.2