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# whisper-small-ar-12hrsdarijadata-April29

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: 0.9985
- Wer: 77.7026
- Cer: 48.3376

## 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: 1.25e-06
- 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: 300
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 1.8036        | 0.38  | 250  | 1.4314          | 92.8372 | 55.4587 |
| 1.3528        | 0.75  | 500  | 1.1339          | 79.2413 | 48.2563 |
| 1.1316        | 1.13  | 750  | 1.0272          | 76.8802 | 49.5272 |
| 1.1439        | 1.51  | 1000 | 0.9985          | 77.7026 | 48.3376 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.12.1.dev0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "whisper-small-ar-12hrsdarijadata-April29", "results": []}]}
transformers pytorch whisper automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #whisper #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

whisper-small-ar-12hrsdarijadata-April29
========================================


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: 0.9985
* Wer: 77.7026
* Cer: 48.3376


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: 1.25e-06
* 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: 300
* training\_steps: 1000
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.0+cu118
* Datasets 2.12.1.dev0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1.25e-06
* 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: 300
* training\_steps: 1000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.0+cu118
* Datasets 2.12.1.dev0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #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: 1.25e-06
* 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: 300
* training\_steps: 1000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.0+cu118
* Datasets 2.12.1.dev0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #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: 1.25e-06
* 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: 300
* training\_steps: 1000
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.0+cu118
* Datasets 2.12.1.dev0
* Tokenizers 0.13.3