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# wav2vec2-large-xls-r-300m-urdu-cv-10

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_10_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5959
- Wer: 0.3946

## 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: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 20.8724       | 0.25  | 32   | 18.0006         | 1.0    |
| 10.984        | 0.5   | 64   | 6.8001          | 1.0    |
| 5.7792        | 0.74  | 96   | 4.9273          | 1.0    |
| 4.2891        | 0.99  | 128  | 3.8379          | 1.0    |
| 3.4937        | 1.24  | 160  | 3.2877          | 1.0    |
| 3.1605        | 1.49  | 192  | 3.1198          | 1.0    |
| 3.0874        | 1.74  | 224  | 3.0542          | 1.0    |
| 3.0363        | 1.98  | 256  | 3.0063          | 0.9999 |
| 2.9776        | 2.23  | 288  | 2.9677          | 1.0    |
| 2.8168        | 2.48  | 320  | 2.4189          | 1.0000 |
| 2.0575        | 2.73  | 352  | 1.5330          | 0.8520 |
| 1.4248        | 2.98  | 384  | 1.1747          | 0.7519 |
| 1.1354        | 3.22  | 416  | 0.9837          | 0.7047 |
| 1.0049        | 3.47  | 448  | 0.9414          | 0.6631 |
| 0.956         | 3.72  | 480  | 0.8948          | 0.6606 |
| 0.8906        | 3.97  | 512  | 0.8381          | 0.6291 |
| 0.7587        | 4.22  | 544  | 0.7714          | 0.5898 |
| 0.7534        | 4.47  | 576  | 0.8237          | 0.5908 |
| 0.7203        | 4.71  | 608  | 0.7731          | 0.5758 |
| 0.6876        | 4.96  | 640  | 0.7467          | 0.5390 |
| 0.5825        | 5.21  | 672  | 0.6940          | 0.5401 |
| 0.5565        | 5.46  | 704  | 0.6826          | 0.5248 |
| 0.5598        | 5.71  | 736  | 0.6387          | 0.5204 |
| 0.5289        | 5.95  | 768  | 0.6432          | 0.4956 |
| 0.4565        | 6.2   | 800  | 0.6643          | 0.4876 |
| 0.4576        | 6.45  | 832  | 0.6295          | 0.4758 |
| 0.4265        | 6.7   | 864  | 0.6227          | 0.4673 |
| 0.4359        | 6.95  | 896  | 0.6077          | 0.4598 |
| 0.3576        | 7.19  | 928  | 0.5800          | 0.4477 |
| 0.3612        | 7.44  | 960  | 0.5837          | 0.4500 |
| 0.345         | 7.69  | 992  | 0.5892          | 0.4466 |
| 0.3707        | 7.94  | 1024 | 0.6217          | 0.4380 |
| 0.3269        | 8.19  | 1056 | 0.5964          | 0.4412 |
| 0.2974        | 8.43  | 1088 | 0.6116          | 0.4394 |
| 0.2932        | 8.68  | 1120 | 0.5764          | 0.4235 |
| 0.2854        | 8.93  | 1152 | 0.5757          | 0.4239 |
| 0.2651        | 9.18  | 1184 | 0.5798          | 0.4253 |
| 0.2508        | 9.43  | 1216 | 0.5750          | 0.4316 |
| 0.238         | 9.67  | 1248 | 0.6038          | 0.4232 |
| 0.2454        | 9.92  | 1280 | 0.5781          | 0.4078 |
| 0.2196        | 10.17 | 1312 | 0.5931          | 0.4178 |
| 0.2036        | 10.42 | 1344 | 0.6134          | 0.4116 |
| 0.2087        | 10.67 | 1376 | 0.5831          | 0.4146 |
| 0.1908        | 10.91 | 1408 | 0.5987          | 0.4159 |
| 0.1751        | 11.16 | 1440 | 0.5968          | 0.4065 |
| 0.1726        | 11.41 | 1472 | 0.6037          | 0.4119 |
| 0.1728        | 11.66 | 1504 | 0.5961          | 0.4011 |
| 0.1772        | 11.91 | 1536 | 0.5903          | 0.3972 |
| 0.1647        | 12.16 | 1568 | 0.5960          | 0.4024 |
| 0.1506        | 12.4  | 1600 | 0.5986          | 0.3933 |
| 0.1383        | 12.65 | 1632 | 0.5893          | 0.3938 |
| 0.1433        | 12.9  | 1664 | 0.5999          | 0.3975 |
| 0.1356        | 13.15 | 1696 | 0.6035          | 0.3982 |
| 0.1431        | 13.4  | 1728 | 0.5997          | 0.4042 |
| 0.1346        | 13.64 | 1760 | 0.6018          | 0.4003 |
| 0.1363        | 13.89 | 1792 | 0.5891          | 0.3969 |
| 0.1323        | 14.14 | 1824 | 0.5983          | 0.3925 |
| 0.1196        | 14.39 | 1856 | 0.6003          | 0.3939 |
| 0.1266        | 14.64 | 1888 | 0.5997          | 0.3941 |
| 0.1269        | 14.88 | 1920 | 0.5959          | 0.3946 |


### Framework versions

- Transformers 4.21.1
- Pytorch 1.11.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["common_voice_10_0"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-urdu-cv-10", "results": []}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer dataset:common_voice_10_0 license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice_10_0 #license-apache-2.0 #endpoints_compatible #region-us 

wav2vec2-large-xls-r-300m-urdu-cv-10
====================================


This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common\_voice\_10\_0 dataset.
It achieves the following results on the evaluation set:


* Loss: 0.5959
* Wer: 0.3946


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: 15
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.21.1
* Pytorch 1.11.0+cu113
* Datasets 2.4.0
* 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: 15
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.11.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice_10_0 #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: 15
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.11.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice_10_0 #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: 15
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.21.1
* Pytorch 1.11.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1