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

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: 0.0021
- Wer: 0.0191
- Cer: 0.0072

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 17.5531       | 1.0   | 51   | 5.2205          | 1.0    | 1.0    |
| 3.9441        | 2.0   | 102  | 3.1378          | 1.0    | 1.0    |
| 3.1686        | 3.0   | 153  | 3.1191          | 1.0    | 1.0    |
| 3.1558        | 4.0   | 204  | 3.1101          | 1.0    | 1.0    |
| 3.1286        | 5.0   | 255  | 3.0171          | 1.0    | 1.0    |
| 3.0755        | 6.0   | 306  | 2.9542          | 1.0    | 1.0    |
| 2.9533        | 7.0   | 357  | 2.8221          | 1.0    | 1.0    |
| 2.5924        | 8.0   | 408  | 2.1453          | 1.0    | 0.9771 |
| 1.8657        | 9.0   | 459  | 1.1540          | 0.9094 | 0.7057 |
| 0.9519        | 10.0  | 510  | 0.4219          | 0.6767 | 0.2782 |
| 0.4752        | 11.0  | 561  | 0.1646          | 0.3416 | 0.0870 |
| 0.2402        | 12.0  | 612  | 0.0551          | 0.0899 | 0.0255 |
| 0.1512        | 13.0  | 663  | 0.0307          | 0.0586 | 0.0167 |
| 0.0906        | 14.0  | 714  | 0.0172          | 0.0541 | 0.0161 |
| 0.0711        | 15.0  | 765  | 0.0141          | 0.0444 | 0.0125 |
| 0.0561        | 16.0  | 816  | 0.0114          | 0.0269 | 0.0065 |
| 0.048         | 17.0  | 867  | 0.0090          | 0.0338 | 0.0110 |
| 0.0452        | 18.0  | 918  | 0.0072          | 0.0235 | 0.0080 |
| 0.0349        | 19.0  | 969  | 0.0073          | 0.0207 | 0.0062 |
| 0.0333        | 20.0  | 1020 | 0.0054          | 0.0183 | 0.0055 |
| 0.0275        | 21.0  | 1071 | 0.0050          | 0.0280 | 0.0087 |
| 0.0262        | 22.0  | 1122 | 0.0039          | 0.0251 | 0.0088 |
| 0.0241        | 23.0  | 1173 | 0.0039          | 0.0302 | 0.0110 |
| 0.0216        | 24.0  | 1224 | 0.0035          | 0.0243 | 0.0086 |
| 0.019         | 25.0  | 1275 | 0.0033          | 0.0250 | 0.0091 |
| 0.0178        | 26.0  | 1326 | 0.0027          | 0.0238 | 0.0089 |
| 0.0169        | 27.0  | 1377 | 0.0025          | 0.0220 | 0.0080 |
| 0.0168        | 28.0  | 1428 | 0.0024          | 0.0175 | 0.0060 |
| 0.015         | 29.0  | 1479 | 0.0021          | 0.0194 | 0.0071 |
| 0.0131        | 30.0  | 1530 | 0.0021          | 0.0191 | 0.0072 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-Arabic-colab", "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-colab
======================================


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: 0.0021
* Wer: 0.0191
* Cer: 0.0072


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 2.10.0
* 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 2.10.0
* 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 2.10.0
* 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 2.10.0
* Tokenizers 0.13.2