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# wav2vec2-large-xls-r-300m-Arabic

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0028
- Wer: 0.0691
- Cer: 0.0318

## 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: 0.0005
- train_batch_size: 16
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- num_epochs: 30.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 17.5167       | 1.0   | 51   | 4.8815          | 1.0    | 1.0    |
| 4.0416        | 2.0   | 102  | 3.1278          | 1.0    | 1.0    |
| 3.1594        | 3.0   | 153  | 3.1154          | 1.0    | 1.0    |
| 3.1534        | 4.0   | 204  | 3.0524          | 1.0    | 1.0    |
| 3.0361        | 5.0   | 255  | 2.8827          | 1.0    | 1.0    |
| 2.799         | 6.0   | 306  | 2.4063          | 1.0    | 0.9571 |
| 1.9731        | 7.0   | 357  | 1.0794          | 0.9762 | 0.5933 |
| 0.7265        | 8.0   | 408  | 0.2350          | 0.4686 | 0.1378 |
| 0.2788        | 9.0   | 459  | 0.0527          | 0.1055 | 0.0265 |
| 0.1396        | 10.0  | 510  | 0.0263          | 0.1063 | 0.0386 |
| 0.0891        | 11.0  | 561  | 0.0245          | 0.0829 | 0.0247 |
| 0.0667        | 12.0  | 612  | 0.0119          | 0.0368 | 0.0091 |
| 0.0594        | 13.0  | 663  | 0.0154          | 0.0405 | 0.0113 |
| 0.0467        | 14.0  | 714  | 0.0109          | 0.0509 | 0.0203 |
| 0.0354        | 15.0  | 765  | 0.0129          | 0.0818 | 0.0320 |
| 0.0332        | 16.0  | 816  | 0.0086          | 0.0933 | 0.0486 |
| 0.0283        | 17.0  | 867  | 0.0135          | 0.0970 | 0.0431 |
| 0.0244        | 18.0  | 918  | 0.0083          | 0.0650 | 0.0276 |
| 0.0268        | 19.0  | 969  | 0.0071          | 0.0286 | 0.0101 |
| 0.0245        | 20.0  | 1020 | 0.0058          | 0.0320 | 0.0120 |
| 0.0206        | 21.0  | 1071 | 0.0031          | 0.1059 | 0.0455 |
| 0.0162        | 22.0  | 1122 | 0.0050          | 0.0699 | 0.0292 |
| 0.0152        | 23.0  | 1173 | 0.0054          | 0.0517 | 0.0192 |
| 0.014         | 24.0  | 1224 | 0.0037          | 0.0654 | 0.0266 |
| 0.0161        | 25.0  | 1275 | 0.0024          | 0.0320 | 0.0127 |
| 0.0156        | 26.0  | 1326 | 0.0027          | 0.0565 | 0.0244 |
| 0.0122        | 27.0  | 1377 | 0.0036          | 0.0587 | 0.0260 |
| 0.0105        | 28.0  | 1428 | 0.0026          | 0.0494 | 0.0216 |
| 0.0114        | 29.0  | 1479 | 0.0028          | 0.0613 | 0.0283 |
| 0.0087        | 30.0  | 1530 | 0.0028          | 0.0691 | 0.0318 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2

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

wav2vec2-large-xls-r-300m-Arabic
================================


This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0028
* Wer: 0.0691
* Cer: 0.0318


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: 0.0005
* train\_batch\_size: 16
* eval\_batch\_size: 6
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 250
* num\_epochs: 30.0
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0005
* train\_batch\_size: 16
* eval\_batch\_size: 6
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 250
* num\_epochs: 30.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #wav2vec2 #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: 0.0005
* train\_batch\_size: 16
* eval\_batch\_size: 6
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 250
* num\_epochs: 30.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #wav2vec2 #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: 0.0005
* train\_batch\_size: 16
* eval\_batch\_size: 6
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 250
* num\_epochs: 30.0
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2