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# Whisper Small Turkish

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 tr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2576
- Wer: 16.6327
- Cer: 4.2853

## 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|
| 0.1412        | 0.08  | 400  | 0.2656          | 19.8335 | 5.2393 |
| 0.0851        | 1.03  | 800  | 0.2382          | 18.6300 | 4.8916 |
| 0.0525        | 1.11  | 1200 | 0.2532          | 19.1696 | 5.2238 |
| 0.0163        | 2.07  | 1600 | 0.2447          | 17.2014 | 4.5840 |
| 0.0202        | 3.02  | 2000 | 0.2472          | 17.1063 | 4.4935 |
| 0.0075        | 3.1   | 2400 | 0.2503          | 17.0151 | 4.4318 |
| 0.0039        | 4.05  | 2800 | 0.2514          | 16.7433 | 4.3655 |
| 0.0038        | 5.01  | 3200 | 0.2565          | 16.8870 | 4.3582 |
| 0.0023        | 5.09  | 3600 | 0.2590          | 16.6987 | 4.3337 |
| 0.0013        | 6.04  | 4000 | 0.2576          | 16.6327 | 4.2853 |
| 0.0011        | 6.12  | 4400 | 0.2647          | 16.9122 | 4.3556 |
| 0.001         | 7.07  | 4800 | 0.2615          | 16.6346 | 4.2839 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2

{"language": ["tr"], "license": "apache-2.0", "tags": ["whisper", "generated_from_trainer"], "datasets": ["mozilla-foundation/common_voice_11_0"], "metrics": ["wer"], "model-index": [{"name": "Whisper Small Turkish", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "mozilla-foundation/common_voice_11_0 tr", "type": "mozilla-foundation/common_voice_11_0", "config": "tr", "split": "test", "args": "tr"}, "metrics": [{"type": "wer", "value": 16.632698616044568, "name": "Wer"}]}]}]}
transformers pytorch tensorboard whisper automatic-speech-recognition generated_from_trainer tr 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 #generated_from_trainer #tr #dataset-mozilla-foundation/common_voice_11_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 

Whisper Small Turkish
=====================


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


* Loss: 0.2576
* Wer: 16.6327
* Cer: 4.2853


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: 5000
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.26.0.dev0
* Pytorch 1.13.1+cu117
* Datasets 2.8.1.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: 5000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.0.dev0
* Pytorch 1.13.1+cu117
* Datasets 2.8.1.dev0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #generated_from_trainer #tr #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: 5000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.0.dev0
* Pytorch 1.13.1+cu117
* Datasets 2.8.1.dev0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #generated_from_trainer #tr #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: 5000
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.26.0.dev0
* Pytorch 1.13.1+cu117
* Datasets 2.8.1.dev0
* Tokenizers 0.13.2