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

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m).
It achieves the following results on the evaluation set:
- Loss: 0.5285
- Wer: 0.1702

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 35
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 16.9618       | 0.74  | 32   | 15.0745         | 1.0    |
| 9.1928        | 1.49  | 64   | 5.9361          | 1.0    |
| 4.9307        | 2.23  | 96   | 4.2924          | 1.0    |
| 3.8917        | 2.98  | 128  | 3.5873          | 1.0    |
| 3.3867        | 3.72  | 160  | 3.2594          | 1.0    |
| 3.2107        | 4.47  | 192  | 3.1718          | 1.0    |
| 3.1395        | 5.21  | 224  | 3.1281          | 1.0    |
| 3.115         | 5.95  | 256  | 3.1238          | 1.0    |
| 3.0801        | 6.7   | 288  | 3.0674          | 1.0    |
| 2.9725        | 7.44  | 320  | 2.8277          | 1.0    |
| 2.4159        | 8.19  | 352  | 1.7186          | 0.9036 |
| 1.3377        | 8.93  | 384  | 1.0271          | 0.6433 |
| 0.8591        | 9.67  | 416  | 0.8087          | 0.5441 |
| 0.726         | 10.42 | 448  | 0.7263          | 0.4634 |
| 0.6242        | 11.16 | 480  | 0.6783          | 0.4156 |
| 0.5417        | 11.91 | 512  | 0.6611          | 0.4305 |
| 0.4784        | 12.65 | 544  | 0.6300          | 0.3926 |
| 0.4198        | 13.4  | 576  | 0.5646          | 0.3499 |
| 0.3798        | 14.14 | 608  | 0.5919          | 0.3229 |
| 0.3356        | 14.88 | 640  | 0.5715          | 0.3369 |
| 0.2954        | 15.63 | 672  | 0.5325          | 0.2728 |
| 0.264         | 16.37 | 704  | 0.5535          | 0.2689 |
| 0.2535        | 17.12 | 736  | 0.5467          | 0.2366 |
| 0.2277        | 17.86 | 768  | 0.5219          | 0.2345 |
| 0.2141        | 18.6  | 800  | 0.5314          | 0.2487 |
| 0.2036        | 19.35 | 832  | 0.5382          | 0.2236 |
| 0.2021        | 20.09 | 864  | 0.5038          | 0.1922 |
| 0.1676        | 20.84 | 896  | 0.5238          | 0.2033 |
| 0.1544        | 21.58 | 928  | 0.5069          | 0.1866 |
| 0.1512        | 22.33 | 960  | 0.5045          | 0.1965 |
| 0.1512        | 23.07 | 992  | 0.5167          | 0.1862 |
| 0.1399        | 23.81 | 1024 | 0.5236          | 0.1840 |
| 0.1291        | 24.56 | 1056 | 0.5234          | 0.1957 |
| 0.1274        | 25.3  | 1088 | 0.5348          | 0.1943 |
| 0.127         | 26.05 | 1120 | 0.4978          | 0.1719 |
| 0.1105        | 26.79 | 1152 | 0.5067          | 0.1767 |
| 0.1069        | 27.53 | 1184 | 0.5150          | 0.1758 |
| 0.1058        | 28.28 | 1216 | 0.5218          | 0.1844 |
| 0.0999        | 29.02 | 1248 | 0.5375          | 0.1852 |
| 0.0964        | 29.77 | 1280 | 0.5373          | 0.1843 |
| 0.0971        | 30.51 | 1312 | 0.5190          | 0.1776 |
| 0.0906        | 31.26 | 1344 | 0.5217          | 0.1747 |
| 0.0909        | 32.0  | 1376 | 0.5204          | 0.1778 |
| 0.0784        | 32.74 | 1408 | 0.5336          | 0.1756 |
| 0.0823        | 33.49 | 1440 | 0.5281          | 0.1699 |
| 0.0834        | 34.23 | 1472 | 0.5292          | 0.1700 |
| 0.0827        | 34.98 | 1504 | 0.5285          | 0.1702 |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1

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

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


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


* Loss: 0.5285
* Wer: 0.1702


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
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 35
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 35
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #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: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 35
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #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: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 35
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1