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# wav2vec2-large-xls-r-300m-Arabic-phoneme

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0335
- Per: 0.0199
- Wer: 0.0225

## 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: 6
- 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: 30.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Per    | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 5.3718        | 1.0   | 102  | 2.1140          | 1.0    | 1.0    |
| 2.036         | 2.0   | 204  | 2.0637          | 1.0    | 1.0    |
| 2.0175        | 3.0   | 306  | 2.1252          | 1.0    | 1.0    |
| 1.9463        | 4.0   | 408  | 1.7014          | 0.9942 | 0.9887 |
| 1.702         | 5.0   | 510  | 1.7257          | 0.9944 | 0.9892 |
| 1.6475        | 6.0   | 612  | 1.5855          | 0.9897 | 0.9798 |
| 1.4766        | 7.0   | 714  | 1.2777          | 0.9787 | 0.9641 |
| 1.0363        | 8.0   | 816  | 0.7926          | 0.7738 | 0.7731 |
| 0.5964        | 9.0   | 918  | 0.4220          | 0.3994 | 0.4133 |
| 0.3437        | 10.0  | 1020 | 0.2307          | 0.1387 | 0.1549 |
| 0.2052        | 11.0  | 1122 | 0.1587          | 0.0645 | 0.0738 |
| 0.1509        | 12.0  | 1224 | 0.1314          | 0.0464 | 0.0544 |
| 0.1256        | 13.0  | 1326 | 0.1070          | 0.0448 | 0.0518 |
| 0.0935        | 14.0  | 1428 | 0.0854          | 0.0394 | 0.0452 |
| 0.0779        | 15.0  | 1530 | 0.0896          | 0.0376 | 0.0440 |
| 0.0674        | 16.0  | 1632 | 0.0625          | 0.0255 | 0.0306 |
| 0.0558        | 17.0  | 1734 | 0.0573          | 0.0270 | 0.0318 |
| 0.0492        | 18.0  | 1836 | 0.0542          | 0.0248 | 0.0288 |
| 0.0486        | 19.0  | 1938 | 0.0631          | 0.0336 | 0.0369 |
| 0.047         | 20.0  | 2040 | 0.0482          | 0.0255 | 0.0290 |
| 0.0432        | 21.0  | 2142 | 0.0470          | 0.0262 | 0.0307 |
| 0.0433        | 22.0  | 2244 | 0.0460          | 0.0250 | 0.0290 |
| 0.0367        | 23.0  | 2346 | 0.0450          | 0.0253 | 0.0295 |
| 0.0343        | 24.0  | 2448 | 0.0444          | 0.0254 | 0.0283 |
| 0.0292        | 25.0  | 2550 | 0.0427          | 0.0248 | 0.0283 |
| 0.0261        | 26.0  | 2652 | 0.0409          | 0.0220 | 0.0250 |
| 0.025         | 27.0  | 2754 | 0.0360          | 0.0221 | 0.0251 |
| 0.0236        | 28.0  | 2856 | 0.0350          | 0.0208 | 0.0231 |
| 0.0222        | 29.0  | 2958 | 0.0338          | 0.0199 | 0.0222 |
| 0.0202        | 30.0  | 3060 | 0.0335          | 0.0199 | 0.0225 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 1.18.3
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "base_model": "facebook/wav2vec2-xls-r-300m", "model-index": [{"name": "wav2vec2-large-xls-r-300m-Arabic-phoneme", "results": []}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer base_model:facebook/wav2vec2-xls-r-300m license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #base_model-facebook/wav2vec2-xls-r-300m #license-apache-2.0 #endpoints_compatible #region-us 

wav2vec2-large-xls-r-300m-Arabic-phoneme
========================================


This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0335
* Per: 0.0199
* Wer: 0.0225


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: 6
* 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: 30.0


### Training results



### Framework versions


* Transformers 4.33.1
* Pytorch 2.0.1+cu118
* Datasets 1.18.3
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0005
* train\_batch\_size: 8
* eval\_batch\_size: 6
* 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: 30.0 ### Training results ### Framework versions


* Transformers 4.33.1
* Pytorch 2.0.1+cu118
* Datasets 1.18.3
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #base_model-facebook/wav2vec2-xls-r-300m #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: 6
* 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: 30.0 ### Training results ### Framework versions


* Transformers 4.33.1
* Pytorch 2.0.1+cu118
* Datasets 1.18.3
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #base_model-facebook/wav2vec2-xls-r-300m #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: 6
* 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: 30.0### Training results### Framework versions


* Transformers 4.33.1
* Pytorch 2.0.1+cu118
* Datasets 1.18.3
* Tokenizers 0.13.3