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# 

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_9_0 - UR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4147
- Wer: 0.3172
- Cer: 0.1050

## 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: 7.5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 5108
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 3.2894        | 7.83  | 400  | 3.1501          | 1.0    | 1.0    |
| 1.8586        | 15.68 | 800  | 0.8871          | 0.6721 | 0.2402 |
| 1.3431        | 23.52 | 1200 | 0.5813          | 0.5502 | 0.1939 |
| 1.2052        | 31.37 | 1600 | 0.4956          | 0.4788 | 0.1665 |
| 1.1097        | 39.21 | 2000 | 0.4447          | 0.4143 | 0.1397 |
| 1.0528        | 47.06 | 2400 | 0.4439          | 0.3961 | 0.1333 |
| 0.9939        | 54.89 | 2800 | 0.4348          | 0.4014 | 0.1379 |
| 0.9441        | 62.74 | 3200 | 0.4236          | 0.3653 | 0.1223 |
| 0.913         | 70.58 | 3600 | 0.4309          | 0.3475 | 0.1157 |
| 0.8678        | 78.43 | 4000 | 0.4270          | 0.3337 | 0.1110 |
| 0.8414        | 86.27 | 4400 | 0.4158          | 0.3220 | 0.1070 |
| 0.817         | 94.12 | 4800 | 0.4185          | 0.3231 | 0.1072 |


### Framework versions

- Transformers 4.19.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.1.1.dev0
- Tokenizers 0.12.1

{"language": ["ur"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_9_0", "generated_from_trainer"], "datasets": ["mozilla-foundation/common_voice_9_0"], "metrics": ["wer"], "model-index": [{"name": "XLS-R-300M - Urdu", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Speech Recognition"}, "dataset": {"name": "Common Voice 9", "type": "mozilla-foundation/common_voice_9_0", "args": "ur"}, "metrics": [{"type": "wer", "value": 23.75, "name": "Test WER"}, {"type": "cer", "value": 8.31, "name": "Test CER"}]}]}]}
transformers pytorch wav2vec2 automatic-speech-recognition mozilla-foundation/common_voice_9_0 generated_from_trainer ur dataset:mozilla-foundation/common_voice_9_0 license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_9_0 #generated_from_trainer #ur #dataset-mozilla-foundation/common_voice_9_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 


This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_9\_0 - UR dataset.
It achieves the following results on the evaluation set:


* Loss: 0.4147
* Wer: 0.3172
* Cer: 0.1050


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: 7.5e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* training\_steps: 5108
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.19.0.dev0
* Pytorch 1.11.0+cu102
* Datasets 2.1.1.dev0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 7.5e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* training\_steps: 5108
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.19.0.dev0
* Pytorch 1.11.0+cu102
* Datasets 2.1.1.dev0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_9_0 #generated_from_trainer #ur #dataset-mozilla-foundation/common_voice_9_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 7.5e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* training\_steps: 5108
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.19.0.dev0
* Pytorch 1.11.0+cu102
* Datasets 2.1.1.dev0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_9_0 #generated_from_trainer #ur #dataset-mozilla-foundation/common_voice_9_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 7.5e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* training\_steps: 5108
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.19.0.dev0
* Pytorch 1.11.0+cu102
* Datasets 2.1.1.dev0
* Tokenizers 0.12.1