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# Whisper Small Synthesized Turkish

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the synthesized_squad dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2564
- Wer: 13.7267

## 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
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 1.276         | 1.04  | 100  | 0.5859          | 92.8836 |
| 0.436         | 2.08  | 200  | 0.3916          | 19.5285 |
| 0.218         | 3.12  | 300  | 0.2345          | 13.2453 |
| 0.0903        | 4.17  | 400  | 0.2332          | 12.9737 |
| 0.0517        | 5.21  | 500  | 0.2360          | 14.3439 |
| 0.0302        | 6.25  | 600  | 0.2318          | 14.0415 |
| 0.0223        | 7.29  | 700  | 0.2372          | 13.9674 |
| 0.0085        | 8.33  | 800  | 0.2421          | 12.4738 |
| 0.0084        | 9.38  | 900  | 0.2424          | 12.3750 |
| 0.0043        | 10.42 | 1000 | 0.2421          | 12.8935 |
| 0.0034        | 11.46 | 1100 | 0.2478          | 13.6218 |
| 0.0025        | 12.5  | 1200 | 0.2490          | 14.7327 |
| 0.002         | 13.54 | 1300 | 0.2513          | 13.0910 |
| 0.0019        | 14.58 | 1400 | 0.2521          | 13.2453 |
| 0.0013        | 15.62 | 1500 | 0.2532          | 13.2144 |
| 0.0012        | 16.67 | 1600 | 0.2547          | 13.3132 |
| 0.001         | 17.71 | 1700 | 0.2552          | 13.7514 |
| 0.001         | 18.75 | 1800 | 0.2559          | 13.7452 |
| 0.001         | 19.79 | 1900 | 0.2563          | 13.7514 |
| 0.001         | 20.83 | 2000 | 0.2564          | 13.7267 |


### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"language": ["tr"], "license": "apache-2.0", "tags": ["hf-asr-leaderboard", "generated_from_trainer"], "datasets": ["synthesized_squad"], "metrics": ["wer"], "model-index": [{"name": "Whisper Small Synthesized Turkish", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "synthesized_squad", "type": "synthesized_squad", "split": "None", "args": "config: hi, split: test"}, "metrics": [{"type": "wer", "value": 13.726700407357118, "name": "Wer"}]}]}]}
transformers pytorch tensorboard whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer tr dataset:synthesized_squad license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #hf-asr-leaderboard #generated_from_trainer #tr #dataset-synthesized_squad #license-apache-2.0 #endpoints_compatible #region-us 

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


This model is a fine-tuned version of openai/whisper-small on the synthesized\_squad dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2564
* Wer: 13.7267


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
* lr\_scheduler\_warmup\_steps: 500
* training\_steps: 2000
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.28.0.dev0
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* 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
* lr\_scheduler\_warmup\_steps: 500
* training\_steps: 2000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.0.dev0
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #hf-asr-leaderboard #generated_from_trainer #tr #dataset-synthesized_squad #license-apache-2.0 #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
* lr\_scheduler\_warmup\_steps: 500
* training\_steps: 2000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.0.dev0
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #hf-asr-leaderboard #generated_from_trainer #tr #dataset-synthesized_squad #license-apache-2.0 #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
* lr\_scheduler\_warmup\_steps: 500
* training\_steps: 2000
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.28.0.dev0
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3