
<!-- 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-hlr

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: 0.3824
- Wer: 49.2902

## 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: 0.0001
- 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      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7481        | 0.52  | 100  | 0.2675          | 14.6834  |
| 0.1975        | 1.04  | 200  | 0.2534          | 13.2144  |
| 0.1388        | 1.56  | 300  | 0.2755          | 15.6647  |
| 0.1585        | 2.08  | 400  | 0.3080          | 14.6649  |
| 0.1153        | 2.6   | 500  | 0.3421          | 17.7447  |
| 0.1241        | 3.12  | 600  | 0.3570          | 16.8189  |
| 0.1093        | 3.65  | 700  | 0.3776          | 18.8125  |
| 0.09          | 4.17  | 800  | 0.3859          | 30.0518  |
| 0.0751        | 4.69  | 900  | 0.3874          | 17.3929  |
| 0.0758        | 5.21  | 1000 | 0.3987          | 20.0901  |
| 0.0602        | 5.73  | 1100 | 0.4017          | 17.1460  |
| 0.0568        | 6.25  | 1200 | 0.3824          | 15.6154  |
| 0.0454        | 6.77  | 1300 | 0.3926          | 15.8808  |
| 0.0433        | 7.29  | 1400 | 0.4146          | 16.3869  |
| 0.0341        | 7.81  | 1500 | 0.4078          | 16.1153  |
| 0.0295        | 8.33  | 1600 | 0.4192          | 17.1275  |
| 0.0274        | 8.85  | 1700 | 0.4140          | 16.3745  |
| 0.0246        | 9.38  | 1800 | 0.4077          | 21.0344  |
| 0.0211        | 9.9   | 1900 | 0.4003          | 19.8741  |
| 0.0149        | 10.42 | 2000 | 0.4054          | 108.7335 |
| 0.0172        | 10.94 | 2100 | 0.3917          | 20.6024  |
| 0.0138        | 11.46 | 2200 | 0.3942          | 889.4643 |
| 0.0108        | 11.98 | 2300 | 0.3906          | 55.0673  |
| 0.0099        | 12.5  | 2400 | 0.3834          | 29.9778  |
| 0.0067        | 13.02 | 2500 | 0.3947          | 34.5883  |
| 0.0045        | 13.54 | 2600 | 0.3940          | 20.9789  |
| 0.0035        | 14.06 | 2700 | 0.3911          | 15.6462  |
| 0.0031        | 14.58 | 2800 | 0.3905          | 18.3990  |
| 0.0018        | 15.1  | 2900 | 0.3919          | 16.3190  |
| 0.0011        | 15.62 | 3000 | 0.3906          | 18.0286  |
| 0.001         | 16.15 | 3100 | 0.3911          | 17.6521  |
| 0.0006        | 16.67 | 3200 | 0.3813          | 27.6879  |
| 0.0007        | 17.19 | 3300 | 0.3800          | 45.7536  |
| 0.0003        | 17.71 | 3400 | 0.3805          | 51.2529  |
| 0.0001        | 18.23 | 3500 | 0.3815          | 51.7282  |
| 0.0001        | 18.75 | 3600 | 0.3821          | 47.0065  |
| 0.0002        | 19.27 | 3700 | 0.3821          | 45.8585  |
| 0.0001        | 19.79 | 3800 | 0.3823          | 47.7904  |
| 0.0001        | 20.31 | 3900 | 0.3824          | 49.2594  |
| 0.0003        | 20.83 | 4000 | 0.3824          | 49.2902  |


### Framework versions

- Transformers 4.28.0
- 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-hlr", "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-hlr
======================================


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: 0.3824
* Wer: 49.2902


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: 0.0001
* 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
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* 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
* 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: 0.0001
* 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
* 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: 0.0001
* 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
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3