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

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: 0.7493
- Per: 0.1979

## 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: 2
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 1.9601        | 1.0   | 2187  | 1.7221          | 0.9190 |
| 1.307         | 2.0   | 4374  | 1.0964          | 0.4532 |
| 0.9363        | 3.0   | 6561  | 0.9163          | 0.3469 |
| 0.7942        | 4.0   | 8748  | 0.8432          | 0.3037 |
| 0.7           | 5.0   | 10935 | 0.7827          | 0.2881 |
| 0.6274        | 6.0   | 13122 | 0.7456          | 0.2713 |
| 0.5692        | 7.0   | 15309 | 0.6924          | 0.2572 |
| 0.5203        | 8.0   | 17496 | 0.6521          | 0.2491 |
| 0.4853        | 9.0   | 19683 | 0.6583          | 0.2420 |
| 0.4448        | 10.0  | 21870 | 0.6580          | 0.2312 |
| 0.4134        | 11.0  | 24057 | 0.6313          | 0.2380 |
| 0.389         | 12.0  | 26244 | 0.6099          | 0.2225 |
| 0.3644        | 13.0  | 28431 | 0.6238          | 0.2239 |
| 0.3432        | 14.0  | 30618 | 0.6369          | 0.2195 |
| 0.3191        | 15.0  | 32805 | 0.6391          | 0.2164 |
| 0.2992        | 16.0  | 34992 | 0.6314          | 0.2164 |
| 0.2827        | 17.0  | 37179 | 0.6385          | 0.2143 |
| 0.2666        | 18.0  | 39366 | 0.6330          | 0.2159 |
| 0.2479        | 19.0  | 41553 | 0.6653          | 0.2125 |
| 0.2341        | 20.0  | 43740 | 0.6692          | 0.2165 |
| 0.2209        | 21.0  | 45927 | 0.6656          | 0.2199 |
| 0.2075        | 22.0  | 48114 | 0.6669          | 0.2104 |
| 0.1955        | 23.0  | 50301 | 0.6830          | 0.2044 |
| 0.1825        | 24.0  | 52488 | 0.6973          | 0.2065 |
| 0.1758        | 25.0  | 54675 | 0.7265          | 0.2013 |
| 0.1644        | 26.0  | 56862 | 0.7416          | 0.2040 |
| 0.1571        | 27.0  | 59049 | 0.7202          | 0.2007 |
| 0.1489        | 28.0  | 61236 | 0.7224          | 0.2019 |
| 0.1432        | 29.0  | 63423 | 0.7357          | 0.1988 |
| 0.1373        | 30.0  | 65610 | 0.7493          | 0.1979 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 1.18.3
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "facebook/wav2vec2-xls-r-300m", "model-index": [{"name": "wav2vec2-large-xls-r-300m-Arabic-phoneme-based", "results": []}]}
transformers pytorch 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 #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-based
==============================================


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: 0.7493
* Per: 0.1979


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: 2
* eval\_batch\_size: 6
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 8
* 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 4.31.0
* 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: 2
* eval\_batch\_size: 6
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 8
* 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 4.31.0
* Pytorch 2.0.1+cu118
* Datasets 1.18.3
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #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: 2
* eval\_batch\_size: 6
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 8
* 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 4.31.0
* Pytorch 2.0.1+cu118
* Datasets 1.18.3
* Tokenizers 0.13.3