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# wav2vec2-large-xls-r-300m-Arabic-phoneme-undicretics-native-non-native

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2776
- Per: 0.3216

## 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: 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: 250
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Per    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 6.4994        | 0.99  | 63   | 2.7517          | 1.0    |
| 2.3232        | 1.99  | 127  | 2.1722          | 1.0    |
| 2.0242        | 3.0   | 191  | 2.1322          | 1.0    |
| 2.0153        | 4.0   | 255  | 2.1381          | 0.9942 |
| 2.2035        | 4.99  | 318  | 2.1159          | 0.9964 |
| 1.9905        | 5.99  | 382  | 2.1363          | 0.9942 |
| 1.9629        | 7.0   | 446  | 2.0447          | 0.9828 |
| 1.9475        | 8.0   | 510  | 2.1098          | 0.9942 |
| 1.8434        | 8.99  | 573  | 1.7443          | 0.9942 |
| 1.7291        | 9.99  | 637  | 1.7329          | 0.9909 |
| 1.7045        | 11.0  | 701  | 1.7493          | 0.9942 |
| 1.6932        | 12.0  | 765  | 1.7182          | 0.9942 |
| 1.6725        | 12.99 | 828  | 1.6675          | 0.9942 |
| 1.6567        | 13.99 | 892  | 1.6564          | 0.9939 |
| 1.6316        | 15.0  | 956  | 1.6156          | 0.9913 |
| 1.6037        | 16.0  | 1020 | 1.5993          | 0.9924 |
| 1.5907        | 16.99 | 1083 | 1.5591          | 0.9952 |
| 1.5663        | 17.99 | 1147 | 1.5204          | 0.9909 |
| 1.502         | 19.0  | 1211 | 1.4375          | 0.9895 |
| 1.4358        | 20.0  | 1275 | 1.3073          | 0.9883 |
| 1.3647        | 20.99 | 1338 | 1.2088          | 0.9768 |
| 1.1395        | 21.99 | 1402 | 1.0489          | 0.9623 |
| 1.0518        | 23.0  | 1466 | 0.8761          | 0.9380 |
| 0.9232        | 24.0  | 1530 | 0.7407          | 0.8915 |
| 0.8209        | 24.99 | 1593 | 0.6368          | 0.8007 |
| 0.6394        | 25.99 | 1657 | 0.5692          | 0.6804 |
| 0.5786        | 27.0  | 1721 | 0.4750          | 0.5382 |
| 0.5173        | 28.0  | 1785 | 0.4252          | 0.4132 |
| 0.4707        | 28.99 | 1848 | 0.3854          | 0.3962 |
| 0.4516        | 29.65 | 1890 | 0.3751          | 0.3847 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-Arabic-phoneme-undicretics-native-non-native", "results": []}]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

wav2vec2-large-xls-r-300m-Arabic-phoneme-undicretics-native-non-native
======================================================================


This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2776
* Per: 0.3216


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: 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: 250
* num\_epochs: 30
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0005
* 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: 250
* num\_epochs: 30
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0005
* 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: 250
* num\_epochs: 30
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3