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# Whisper Large Arabic

This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the mozilla-foundation/common_voice_11_0 ar dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3231
- Wer: 49.4320

## 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: 8
- eval_batch_size: 2
- 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: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.2472        | 0.1   | 1000  | 0.3719          | 58.9560 |
| 0.2015        | 0.2   | 2000  | 0.3487          | 53.5213 |
| 0.1418        | 1.04  | 3000  | 0.3231          | 49.4320 |
| 0.0921        | 1.14  | 4000  | 0.3284          | 56.1107 |
| 0.0923        | 1.24  | 5000  | 0.3304          | 61.4227 |
| 0.0483        | 2.08  | 6000  | 0.3460          | 55.952  |
| 0.0391        | 2.18  | 7000  | 0.3538          | 51.1067 |
| 0.0228        | 3.02  | 8000  | 0.3493          | 51.82   |
| 0.0206        | 3.12  | 9000  | 0.3729          | 52.4000 |
| 0.018         | 3.22  | 10000 | 0.3676          | 51.296  |


### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.11.1.dev0
- Tokenizers 0.13.2

{"language": ["ar"], "license": "apache-2.0", "tags": ["whisper-event", "generated_from_trainer"], "datasets": ["mozilla-foundation/common_voice_11_0"], "metrics": ["wer"], "model-index": [{"name": "Whisper Large Arabic", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "mozilla-foundation/common_voice_11_0 ar", "type": "mozilla-foundation/common_voice_11_0", "config": "ar", "split": "test", "args": "ar"}, "metrics": [{"type": "wer", "value": 49.431999999999995, "name": "Wer"}]}]}]}
transformers pytorch tensorboard whisper automatic-speech-recognition whisper-event generated_from_trainer ar dataset:mozilla-foundation/common_voice_11_0 license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #whisper-event #generated_from_trainer #ar #dataset-mozilla-foundation/common_voice_11_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 

Whisper Large Arabic
====================


This model is a fine-tuned version of openai/whisper-large on the mozilla-foundation/common\_voice\_11\_0 ar dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3231
* Wer: 49.4320


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: 8
* eval\_batch\_size: 2
* 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: 10000
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.28.0.dev0
* Pytorch 2.0.0+cu117
* Datasets 2.11.1.dev0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 8
* eval\_batch\_size: 2
* 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: 10000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.0.dev0
* Pytorch 2.0.0+cu117
* Datasets 2.11.1.dev0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #whisper-event #generated_from_trainer #ar #dataset-mozilla-foundation/common_voice_11_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 8
* eval\_batch\_size: 2
* 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: 10000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.0.dev0
* Pytorch 2.0.0+cu117
* Datasets 2.11.1.dev0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #whisper-event #generated_from_trainer #ar #dataset-mozilla-foundation/common_voice_11_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 8
* eval\_batch\_size: 2
* 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: 10000
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.28.0.dev0
* Pytorch 2.0.0+cu117
* Datasets 2.11.1.dev0
* Tokenizers 0.13.2