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# wav2vec2-large-xls-r-300m-hi-cv8-b2

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_8_0 - HI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7322
- Wer: 0.3469

### Evaluation Commands

1. To evaluate on mozilla-foundation/common_voice_8_0 with test split

python eval.py --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-hi-cv8-b2 --dataset mozilla-foundation/common_voice_8_0 --config hi --split test --log_outputs

2. To evaluate on speech-recognition-community-v2/dev_data

Hindi language isn't available in speech-recognition-community-v2/dev_data


### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.00025
- 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: 700
- num_epochs: 35
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 9.6226        | 1.04  | 200  | 3.8855          | 1.0    |
| 3.4678        | 2.07  | 400  | 3.4283          | 1.0    |
| 2.3668        | 3.11  | 600  | 1.0743          | 0.7175 |
| 0.7308        | 4.15  | 800  | 0.7663          | 0.5498 |
| 0.4985        | 5.18  | 1000 | 0.6957          | 0.5001 |
| 0.3817        | 6.22  | 1200 | 0.6932          | 0.4866 |
| 0.3281        | 7.25  | 1400 | 0.7034          | 0.4983 |
| 0.2752        | 8.29  | 1600 | 0.6588          | 0.4606 |
| 0.2475        | 9.33  | 1800 | 0.6514          | 0.4328 |
| 0.219         | 10.36 | 2000 | 0.6396          | 0.4176 |
| 0.2036        | 11.4  | 2200 | 0.6867          | 0.4162 |
| 0.1793        | 12.44 | 2400 | 0.6943          | 0.4196 |
| 0.1724        | 13.47 | 2600 | 0.6862          | 0.4260 |
| 0.1554        | 14.51 | 2800 | 0.7615          | 0.4222 |
| 0.151         | 15.54 | 3000 | 0.7058          | 0.4110 |
| 0.1335        | 16.58 | 3200 | 0.7172          | 0.3986 |
| 0.1326        | 17.62 | 3400 | 0.7182          | 0.3923 |
| 0.1225        | 18.65 | 3600 | 0.6995          | 0.3910 |
| 0.1146        | 19.69 | 3800 | 0.7075          | 0.3875 |
| 0.108         | 20.73 | 4000 | 0.7297          | 0.3858 |
| 0.1048        | 21.76 | 4200 | 0.7413          | 0.3850 |
| 0.0979        | 22.8  | 4400 | 0.7452          | 0.3793 |
| 0.0946        | 23.83 | 4600 | 0.7436          | 0.3759 |
| 0.0897        | 24.87 | 4800 | 0.7289          | 0.3754 |
| 0.0854        | 25.91 | 5000 | 0.7271          | 0.3667 |
| 0.0803        | 26.94 | 5200 | 0.7378          | 0.3656 |
| 0.0752        | 27.98 | 5400 | 0.7488          | 0.3680 |
| 0.0718        | 29.02 | 5600 | 0.7185          | 0.3619 |
| 0.0702        | 30.05 | 5800 | 0.7428          | 0.3554 |
| 0.0653        | 31.09 | 6000 | 0.7447          | 0.3559 |
| 0.0638        | 32.12 | 6200 | 0.7327          | 0.3523 |
| 0.058         | 33.16 | 6400 | 0.7339          | 0.3488 |
| 0.0594        | 34.2  | 6600 | 0.7322          | 0.3469 |


### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0

{"language": ["hi"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "robust-speech-event", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-hi-cv8-b2", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Speech Recognition"}, "dataset": {"name": "Common Voice 7", "type": "mozilla-foundation/common_voice_8_0", "args": "hi"}, "metrics": [{"type": "wer", "value": 0.3891350503092403, "name": "Test WER"}, {"type": "cer", "value": 0.13016327327131985, "name": "Test CER"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Robust Speech Event - Dev Data", "type": "speech-recognition-community-v2/dev_data", "args": "hi"}, "metrics": [{"type": "wer", "value": "NA", "name": "Test WER"}, {"type": "cer", "value": "NA", "name": "Test CER"}]}]}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition robust-speech-event hf-asr-leaderboard hi dataset:mozilla-foundation/common_voice_8_0 license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #robust-speech-event #hf-asr-leaderboard #hi #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 

wav2vec2-large-xls-r-300m-hi-cv8-b2
===================================


This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - HI dataset.
It achieves the following results on the evaluation set:


* Loss: 0.7322
* Wer: 0.3469


### Evaluation Commands


1. To evaluate on mozilla-foundation/common\_voice\_8\_0 with test split


python URL --model\_id DrishtiSharma/wav2vec2-large-xls-r-300m-hi-cv8-b2 --dataset mozilla-foundation/common\_voice\_8\_0 --config hi --split test --log\_outputs


2. To evaluate on speech-recognition-community-v2/dev\_data


Hindi language isn't available in speech-recognition-community-v2/dev\_data


### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.00025
* 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: 700
* num\_epochs: 35
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.16.2
* Pytorch 1.10.0+cu111
* Datasets 1.18.3
* Tokenizers 0.11.0



### Evaluation Commands


1. To evaluate on mozilla-foundation/common\_voice\_8\_0 with test split


python URL --model\_id DrishtiSharma/wav2vec2-large-xls-r-300m-hi-cv8-b2 --dataset mozilla-foundation/common\_voice\_8\_0 --config hi --split test --log\_outputs


2. To evaluate on speech-recognition-community-v2/dev\_data


Hindi language isn't available in speech-recognition-community-v2/dev\_data ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.00025
* 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: 700
* num\_epochs: 35
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.16.2
* Pytorch 1.10.0+cu111
* Datasets 1.18.3
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #robust-speech-event #hf-asr-leaderboard #hi #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
 ### Evaluation Commands


1. To evaluate on mozilla-foundation/common\_voice\_8\_0 with test split


python URL --model\_id DrishtiSharma/wav2vec2-large-xls-r-300m-hi-cv8-b2 --dataset mozilla-foundation/common\_voice\_8\_0 --config hi --split test --log\_outputs


2. To evaluate on speech-recognition-community-v2/dev\_data


Hindi language isn't available in speech-recognition-community-v2/dev\_data ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.00025
* 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: 700
* num\_epochs: 35
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.16.2
* Pytorch 1.10.0+cu111
* Datasets 1.18.3
* Tokenizers 0.11.0
passage: TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #robust-speech-event #hf-asr-leaderboard #hi #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
### Evaluation Commands


1. To evaluate on mozilla-foundation/common\_voice\_8\_0 with test split


python URL --model\_id DrishtiSharma/wav2vec2-large-xls-r-300m-hi-cv8-b2 --dataset mozilla-foundation/common\_voice\_8\_0 --config hi --split test --log\_outputs


2. To evaluate on speech-recognition-community-v2/dev\_data


Hindi language isn't available in speech-recognition-community-v2/dev\_data### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.00025
* 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: 700
* num\_epochs: 35
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.16.2
* Pytorch 1.10.0+cu111
* Datasets 1.18.3
* Tokenizers 0.11.0