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# wav2vec2-xls-r-300m-ar

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 - AR dataset.
It achieves the following results on the evaluation set:
- eval_loss: 3.0191
- eval_wer: 1.0
- eval_runtime: 252.2389
- eval_samples_per_second: 30.217
- eval_steps_per_second: 0.476
- epoch: 1.0
- step: 340

## 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: 0.0005
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 5
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0

#### Evaluation Commands

Please use the evaluation script `eval.py` included in the repo.

1. To evaluate on `speech-recognition-community-v2/dev_data`

```bash
python eval.py --model_id nouamanetazi/wav2vec2-xls-r-300m-ar --dataset speech-recognition-community-v2/dev_data --config ar --split validation --chunk_length_s 5.0 --stride_length_s 1.0
```
{"language": ["ar"], "license": "apache-2.0", "tags": ["ar", "automatic-speech-recognition", "common_voice", "generated_from_trainer", "hf-asr-leaderboard", "robust-speech-event"], "datasets": ["common_voice"], "model-index": [{"name": "XLS-R-300M - Arabic", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Robust Speech Event - Dev Data", "type": "speech-recognition-community-v2/dev_data", "args": "ar"}, "metrics": [{"type": "wer", "value": 1.0, "name": "Test WER"}, {"type": "cer", "value": 1.0, "name": "Test CER"}]}]}]}
transformers pytorch wav2vec2 automatic-speech-recognition ar common_voice generated_from_trainer hf-asr-leaderboard robust-speech-event dataset:common_voice license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ar #common_voice #generated_from_trainer #hf-asr-leaderboard #robust-speech-event #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us 




# wav2vec2-xls-r-300m-ar

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the COMMON_VOICE - AR dataset.
It achieves the following results on the evaluation set:
- eval_loss: 3.0191
- eval_wer: 1.0
- eval_runtime: 252.2389
- eval_samples_per_second: 30.217
- eval_steps_per_second: 0.476
- epoch: 1.0
- step: 340

## 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: 0.0005
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 5
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0

#### Evaluation Commands

Please use the evaluation script 'URL' included in the repo.

1. To evaluate on 'speech-recognition-community-v2/dev_data'


# wav2vec2-xls-r-300m-ar

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the COMMON_VOICE - AR dataset.
It achieves the following results on the evaluation set:
- eval_loss: 3.0191
- eval_wer: 1.0
- eval_runtime: 252.2389
- eval_samples_per_second: 30.217
- eval_steps_per_second: 0.476
- epoch: 1.0
- step: 340 ## 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: 0.0005
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 5
- mixed_precision_training: Native AMP ### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0 #### Evaluation Commands

Please use the evaluation script 'URL' included in the repo.

1. To evaluate on 'speech-recognition-community-v2/dev_data'
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ar #common_voice #generated_from_trainer #hf-asr-leaderboard #robust-speech-event #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us 
 # wav2vec2-xls-r-300m-ar

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the COMMON_VOICE - AR dataset.
It achieves the following results on the evaluation set:
- eval_loss: 3.0191
- eval_wer: 1.0
- eval_runtime: 252.2389
- eval_samples_per_second: 30.217
- eval_steps_per_second: 0.476
- epoch: 1.0
- step: 340 ## 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: 0.0005
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 5
- mixed_precision_training: Native AMP ### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0 #### Evaluation Commands

Please use the evaluation script 'URL' included in the repo.

1. To evaluate on 'speech-recognition-community-v2/dev_data'
passage: TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ar #common_voice #generated_from_trainer #hf-asr-leaderboard #robust-speech-event #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us 
# wav2vec2-xls-r-300m-ar

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the COMMON_VOICE - AR dataset.
It achieves the following results on the evaluation set:
- eval_loss: 3.0191
- eval_wer: 1.0
- eval_runtime: 252.2389
- eval_samples_per_second: 30.217
- eval_steps_per_second: 0.476
- epoch: 1.0
- step: 340## 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: 0.0005
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 5
- mixed_precision_training: Native AMP### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0#### Evaluation Commands

Please use the evaluation script 'URL' included in the repo.

1. To evaluate on 'speech-recognition-community-v2/dev_data'