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

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: 0.0204
- Per: 0.0096

## 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: 16
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- num_epochs: 20.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Per    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 8.4892        | 1.0   | 51   | 3.3287          | 1.0    |
| 2.5606        | 1.99  | 102  | 2.0472          | 1.0    |
| 2.0523        | 2.99  | 153  | 2.0184          | 1.0    |
| 1.9865        | 4.0   | 205  | 1.9865          | 1.0    |
| 1.9854        | 5.0   | 256  | 1.9408          | 0.9934 |
| 1.9603        | 5.99  | 307  | 1.9124          | 0.9937 |
| 1.8169        | 6.99  | 358  | 1.6965          | 0.9871 |
| 1.5596        | 8.0   | 410  | 1.4850          | 0.9779 |
| 1.3494        | 9.0   | 461  | 1.1074          | 0.9782 |
| 0.9242        | 9.99  | 512  | 0.6071          | 0.7359 |
| 0.5172        | 10.99 | 563  | 0.2910          | 0.2875 |
| 0.3105        | 12.0  | 615  | 0.1489          | 0.1075 |
| 0.186         | 13.0  | 666  | 0.0938          | 0.0342 |
| 0.1437        | 13.99 | 717  | 0.0809          | 0.0255 |
| 0.1185        | 14.99 | 768  | 0.0665          | 0.0127 |
| 0.0952        | 16.0  | 820  | 0.0409          | 0.0103 |
| 0.0721        | 17.0  | 871  | 0.0291          | 0.0107 |
| 0.0575        | 17.99 | 922  | 0.0228          | 0.0089 |
| 0.0503        | 18.99 | 973  | 0.0216          | 0.0100 |
| 0.0439        | 19.9  | 1020 | 0.0204          | 0.0096 |


### Framework versions

- Transformers 4.30.1
- Pytorch 2.0.1+cu118
- Datasets 1.18.3
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-Arabic-MDD", "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-MDD
====================================


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: 0.0204
* Per: 0.0096


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: 16
* eval\_batch\_size: 6
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 250
* num\_epochs: 20.0


### Training results



### Framework versions


* Transformers 4.30.1
* 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: 16
* eval\_batch\_size: 6
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 250
* num\_epochs: 20.0 ### Training results ### Framework versions


* Transformers 4.30.1
* Pytorch 2.0.1+cu118
* Datasets 1.18.3
* 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: 16
* eval\_batch\_size: 6
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 250
* num\_epochs: 20.0 ### Training results ### Framework versions


* Transformers 4.30.1
* Pytorch 2.0.1+cu118
* Datasets 1.18.3
* Tokenizers 0.13.3