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# 

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - UR dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5614
- Wer: 0.6765

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.9115        | 20.83 | 500  | 1.5400          | 0.7280 |
| 0.1155        | 41.67 | 1000 | 1.5614          | 0.6765 |


### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0
{"language": ["ur"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_7_0", "generated_from_trainer", "sv", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Common Voice 8.0", "type": "mozilla-foundation/common_voice_8_0", "args": "ur"}, "metrics": [{"type": "wer", "value": 67.48, "name": "Test WER"}]}]}]}
transformers pytorch safetensors wav2vec2 automatic-speech-recognition mozilla-foundation/common_voice_7_0 generated_from_trainer sv robust-speech-event model_for_talk hf-asr-leaderboard ur dataset:mozilla-foundation/common_voice_7_0 license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #sv #robust-speech-event #model_for_talk #hf-asr-leaderboard #ur #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us 


This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - UR dataset.
It achieves the following results on the evaluation set:


* Loss: 1.5614
* Wer: 0.6765


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
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 1000
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.1+cu102
* Datasets 1.17.1.dev0
* Tokenizers 0.11.0



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 1000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.1+cu102
* Datasets 1.17.1.dev0
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #safetensors #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #sv #robust-speech-event #model_for_talk #hf-asr-leaderboard #ur #dataset-mozilla-foundation/common_voice_7_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
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 1000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.1+cu102
* Datasets 1.17.1.dev0
* Tokenizers 0.11.0
passage: TAGS
#transformers #pytorch #safetensors #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #sv #robust-speech-event #model_for_talk #hf-asr-leaderboard #ur #dataset-mozilla-foundation/common_voice_7_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
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 1000
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.1+cu102
* Datasets 1.17.1.dev0
* Tokenizers 0.11.0