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# wav2vec2-xls-r-300m-ar

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the ARABIC_SPEECH_CORPUS - NA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3212
- Wer: 0.0636

## 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: 0.0003
- 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: 10000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.0793        | 8.85  | 1000  | 0.1626          | 0.0786 |
| 0.0396        | 17.7  | 2000  | 0.2199          | 0.0807 |
| 0.0285        | 26.55 | 3000  | 0.2289          | 0.0694 |
| 0.021         | 35.4  | 4000  | 0.2662          | 0.0722 |
| 0.0177        | 44.25 | 5000  | 0.2459          | 0.0744 |
| 0.0155        | 53.1  | 6000  | 0.2689          | 0.0679 |
| 0.0149        | 61.95 | 7000  | 0.2760          | 0.0717 |
| 0.0074        | 70.8  | 8000  | 0.3004          | 0.0680 |
| 0.0058        | 79.65 | 9000  | 0.3113          | 0.0650 |
| 0.0033        | 88.5  | 10000 | 0.3212          | 0.0636 |


### Framework versions

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

{"license": "apache-2.0", "tags": ["automatic-speech-recognition", "arabic_speech_corpus", "generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-xls-r-300m-ar", "results": []}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition arabic_speech_corpus generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #arabic_speech_corpus #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

wav2vec2-xls-r-300m-ar
======================


This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the ARABIC\_SPEECH\_CORPUS - NA dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3212
* Wer: 0.0636


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: 0.0003
* 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: 10000


### 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: 0.0003
* 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: 10000 ### 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 #wav2vec2 #automatic-speech-recognition #arabic_speech_corpus #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* 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: 10000 ### 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 #wav2vec2 #automatic-speech-recognition #arabic_speech_corpus #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* 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: 10000### Training results### Framework versions


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