
<!-- 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 Small Arabic- Taqwa

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the tm_data dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5471
- Wer: 52.1387

## 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: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1628        | 5.0   | 500  | 0.5471          | 52.1387 |


### Framework versions

- Transformers 4.29.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"language": ["ar"], "license": "apache-2.0", "tags": ["hf-asr-leaderboard", "generated_from_trainer"], "datasets": ["taqwa92/tm_data"], "metrics": ["wer"], "model-index": [{"name": "Whisper Small Arabic- Taqwa", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "tm_data", "type": "taqwa92/tm_data", "config": "default", "split": "test[:5%]", "args": "config: ar, split: test"}, "metrics": [{"type": "wer", "value": 52.138728323699425, "name": "Wer"}]}]}]}
transformers pytorch tensorboard whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer ar dataset:taqwa92/tm_data license:apache-2.0 model-index endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #hf-asr-leaderboard #generated_from_trainer #ar #dataset-taqwa92/tm_data #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us 

Whisper Small Arabic- Taqwa
===========================


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


* Loss: 0.5471
* Wer: 52.1387


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: 500
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.29.0.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: 500
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.0.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 #ar #dataset-taqwa92/tm_data #license-apache-2.0 #model-index #endpoints_compatible #has_space #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: 500
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.0.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 #ar #dataset-taqwa92/tm_data #license-apache-2.0 #model-index #endpoints_compatible #has_space #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: 500
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.29.0.dev0
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3