
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# whisper-synthesized-turkish-8-hour

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2300
- Wer: 23.0527

## 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: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 1.2682        | 0.52  | 100  | 0.5845          | 99.7901 |
| 0.4591        | 1.04  | 200  | 0.3895          | 21.4541 |
| 0.2482        | 1.56  | 300  | 0.2241          | 12.2145 |
| 0.1554        | 2.08  | 400  | 0.2092          | 11.7825 |
| 0.096         | 2.6   | 500  | 0.2035          | 13.9057 |
| 0.0765        | 3.12  | 600  | 0.2052          | 11.2517 |
| 0.0424        | 3.65  | 700  | 0.2024          | 13.4490 |
| 0.0403        | 4.17  | 800  | 0.2094          | 12.0849 |
| 0.0216        | 4.69  | 900  | 0.2049          | 13.1959 |
| 0.0201        | 5.21  | 1000 | 0.2079          | 12.1034 |
| 0.0101        | 5.73  | 1100 | 0.2073          | 12.5663 |
| 0.0131        | 6.25  | 1200 | 0.2093          | 16.7757 |
| 0.0088        | 6.77  | 1300 | 0.2121          | 16.5165 |
| 0.0073        | 7.29  | 1400 | 0.2142          | 15.3314 |
| 0.0036        | 7.81  | 1500 | 0.2183          | 13.7020 |
| 0.0047        | 8.33  | 1600 | 0.2159          | 16.1647 |
| 0.0038        | 8.85  | 1700 | 0.2166          | 13.7514 |
| 0.0027        | 9.38  | 1800 | 0.2172          | 19.9975 |
| 0.0028        | 9.9   | 1900 | 0.2183          | 18.2385 |
| 0.0015        | 10.42 | 2000 | 0.2196          | 17.4238 |
| 0.0023        | 10.94 | 2100 | 0.2192          | 14.7019 |
| 0.0012        | 11.46 | 2200 | 0.2216          | 15.9919 |
| 0.0017        | 11.98 | 2300 | 0.2215          | 19.6334 |
| 0.001         | 12.5  | 2400 | 0.2219          | 20.5160 |
| 0.0014        | 13.02 | 2500 | 0.2236          | 21.7813 |
| 0.0011        | 13.54 | 2600 | 0.2242          | 23.0897 |
| 0.0009        | 14.06 | 2700 | 0.2276          | 25.0401 |
| 0.001         | 14.58 | 2800 | 0.2269          | 18.7014 |
| 0.001         | 15.1  | 2900 | 0.2265          | 20.8554 |
| 0.0008        | 15.62 | 3000 | 0.2272          | 19.7013 |
| 0.0009        | 16.15 | 3100 | 0.2277          | 26.5831 |
| 0.0007        | 16.67 | 3200 | 0.2290          | 24.3427 |
| 0.0008        | 17.19 | 3300 | 0.2285          | 20.7011 |
| 0.0007        | 17.71 | 3400 | 0.2288          | 21.8738 |
| 0.0007        | 18.23 | 3500 | 0.2290          | 20.7258 |
| 0.0006        | 18.75 | 3600 | 0.2295          | 21.1641 |
| 0.0006        | 19.27 | 3700 | 0.2297          | 23.7625 |
| 0.0007        | 19.79 | 3800 | 0.2301          | 24.4044 |
| 0.0006        | 20.31 | 3900 | 0.2299          | 22.9786 |
| 0.0006        | 20.83 | 4000 | 0.2300          | 23.0527 |


### Framework versions

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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "whisper-synthesized-turkish-8-hour", "results": []}]}
transformers pytorch tensorboard whisper automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

whisper-synthesized-turkish-8-hour
==================================


This model is a fine-tuned version of openai/whisper-small on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2300
* Wer: 23.0527


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: 4000
* 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: 4000
* 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 #generated_from_trainer #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: 4000
* 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 #generated_from_trainer #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: 4000
* 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