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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_7_0 - AR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4502
- Wer: 0.4783

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 2000
- num_epochs: 5.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 4.7972        | 0.43  | 500   | 5.1401          | 1.0    |
| 3.3241        | 0.86  | 1000  | 3.3220          | 1.0    |
| 3.1432        | 1.29  | 1500  | 3.0806          | 0.9999 |
| 2.9297        | 1.72  | 2000  | 2.5678          | 1.0057 |
| 2.2593        | 2.14  | 2500  | 1.1068          | 0.8218 |
| 2.0504        | 2.57  | 3000  | 0.7878          | 0.7114 |
| 1.937         | 3.0   | 3500  | 0.6955          | 0.6450 |
| 1.8491        | 3.43  | 4000  | 0.6452          | 0.6304 |
| 1.803         | 3.86  | 4500  | 0.5961          | 0.6042 |
| 1.7545        | 4.29  | 5000  | 0.5550          | 0.5748 |
| 1.7045        | 4.72  | 5500  | 0.5374          | 0.5743 |
| 1.6733        | 5.15  | 6000  | 0.5337          | 0.5404 |
| 1.6761        | 5.57  | 6500  | 0.5054          | 0.5266 |
| 1.655         | 6.0   | 7000  | 0.4926          | 0.5243 |
| 1.6252        | 6.43  | 7500  | 0.4946          | 0.5183 |
| 1.6209        | 6.86  | 8000  | 0.4915          | 0.5194 |
| 1.5772        | 7.29  | 8500  | 0.4725          | 0.5104 |
| 1.5602        | 7.72  | 9000  | 0.4726          | 0.5097 |
| 1.5783        | 8.15  | 9500  | 0.4667          | 0.4956 |
| 1.5442        | 8.58  | 10000 | 0.4685          | 0.4937 |
| 1.5597        | 9.01  | 10500 | 0.4708          | 0.4957 |
| 1.5406        | 9.43  | 11000 | 0.4539          | 0.4810 |
| 1.5274        | 9.86  | 11500 | 0.4502          | 0.4783 |


### Framework versions

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

{"language": ["ar"], "license": "apache-2.0", "tags": ["ar", "automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "mozilla-foundation/common_voice_7_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Arabic", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Common Voice 7", "type": "mozilla-foundation/common_voice_7_0", "args": "ar"}, "metrics": [{"type": "wer", "value": 47.54, "name": "Test WER"}, {"type": "cer", "value": 17.64, "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": "ar"}, "metrics": [{"type": "wer", "value": 93.72, "name": "Test WER"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Robust Speech Event - Test Data", "type": "speech-recognition-community-v2/eval_data", "args": "ar"}, "metrics": [{"type": "wer", "value": 92.49, "name": "Test WER"}]}]}]}
transformers pytorch wav2vec2 automatic-speech-recognition ar generated_from_trainer hf-asr-leaderboard mozilla-foundation/common_voice_7_0 robust-speech-event dataset:mozilla-foundation/common_voice_7_0 license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ar #generated_from_trainer #hf-asr-leaderboard #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_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\_7\_0 - AR dataset.
It achieves the following results on the evaluation set:


* Loss: 0.4502
* Wer: 0.4783


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: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* 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: 2000
* num\_epochs: 5.0
* 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: 7.5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* 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: 2000
* num\_epochs: 5.0
* 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 #wav2vec2 #automatic-speech-recognition #ar #generated_from_trainer #hf-asr-leaderboard #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_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: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* 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: 2000
* num\_epochs: 5.0
* 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 #wav2vec2 #automatic-speech-recognition #ar #generated_from_trainer #hf-asr-leaderboard #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_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: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* 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: 2000
* num\_epochs: 5.0
* 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