
# Wav2Vec2 XLS-R Adult/Child Indonesian Speech Classifier

Wav2Vec2 XLS-R Adult/Child Indonesian Speech Classifier is an audio classification model based on the [XLS-R](https://arxiv.org/abs/2111.09296) architecture. This model is a fine-tuned version of [wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on a private adult/child Indonesian speech classification dataset.

This model was trained using HuggingFace's PyTorch framework. All training was done on a Tesla P100, provided by Kaggle. Training metrics were logged via Tensorboard.

## Model

| Model                               | #params | Arch. | Training/Validation data (text)                      |
| ----------------------------------- | ------- | ----- | ---------------------------------------------------- |
| `wav2vec2-xls-r-adult-child-id-cls` | 300M    | XLS-R | Adult/Child Indonesian Speech Classification Dataset |

## Evaluation Results

The model achieves the following results on evaluation:

| Dataset                                      | Loss   | Accuracy | F1     |
| -------------------------------------------- | ------ | -------- | ------ |
| Adult/Child Indonesian Speech Classification | 0.1970 | 93.38%   | 0.9307 |

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:

-   `learning_rate`: 3e-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_ratio`: 0.1
-   `num_epochs`: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |   F1   |
| :-----------: | :---: | :--: | :-------------: | :------: | :----: |
|     0.336     |  1.0  | 305  |     0.3146      |  0.8845  | 0.8698 |
|    0.2345     |  2.0  | 610  |     0.2140      |  0.9251  | 0.9202 |
|    0.3215     |  3.0  | 915  |     0.2038      |  0.9315  | 0.9286 |
|    0.2059     |  4.0  | 1220 |     0.1970      |  0.9338  | 0.9307 |

## Disclaimer

Do consider the biases which came from pre-training datasets that may be carried over into the results of this model.

## Authors

Wav2Vec2 XLS-R Adult/Child Indonesian Speech Classifier was trained and evaluated by [Ananto Joyoadikusumo](https://anantoj.github.io/). All computation and development are done on Kaggle.

## Framework versions

-   Transformers 4.18.0
-   Pytorch 1.11.0+cu102
-   Datasets 2.2.0
-   Tokenizers 0.12.1

{"language": "id", "license": "apache-2.0", "tags": ["audio-classification", "generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "wav2vec2-xls-r-adult-child-id-cls", "results": []}]}
transformers pytorch tensorboard wav2vec2 audio-classification generated_from_trainer id arxiv:2111.09296 license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #audio-classification #generated_from_trainer #id #arxiv-2111.09296 #license-apache-2.0 #endpoints_compatible #region-us 

Wav2Vec2 XLS-R Adult/Child Indonesian Speech Classifier
=======================================================


Wav2Vec2 XLS-R Adult/Child Indonesian Speech Classifier is an audio classification model based on the XLS-R architecture. This model is a fine-tuned version of wav2vec2-xls-r-300m on a private adult/child Indonesian speech classification dataset.


This model was trained using HuggingFace's PyTorch framework. All training was done on a Tesla P100, provided by Kaggle. Training metrics were logged via Tensorboard.


Model
-----



Evaluation Results
------------------


The model achieves the following results on evaluation:



Training procedure
------------------


### Training hyperparameters


The following hyperparameters were used during training:


* 'learning\_rate': 3e-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\_ratio': 0.1
* 'num\_epochs': 4


### Training results



Disclaimer
----------


Do consider the biases which came from pre-training datasets that may be carried over into the results of this model.


Authors
-------


Wav2Vec2 XLS-R Adult/Child Indonesian Speech Classifier was trained and evaluated by Ananto Joyoadikusumo. All computation and development are done on Kaggle.


Framework versions
------------------


* Transformers 4.18.0
* Pytorch 1.11.0+cu102
* Datasets 2.2.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* 'learning\_rate': 3e-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\_ratio': 0.1
* 'num\_epochs': 4 ### Training results



Disclaimer
----------


Do consider the biases which came from pre-training datasets that may be carried over into the results of this model.


Authors
-------


Wav2Vec2 XLS-R Adult/Child Indonesian Speech Classifier was trained and evaluated by Ananto Joyoadikusumo. All computation and development are done on Kaggle.


Framework versions
------------------


* Transformers 4.18.0
* Pytorch 1.11.0+cu102
* Datasets 2.2.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #audio-classification #generated_from_trainer #id #arxiv-2111.09296 #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* 'learning\_rate': 3e-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\_ratio': 0.1
* 'num\_epochs': 4 ### Training results



Disclaimer
----------


Do consider the biases which came from pre-training datasets that may be carried over into the results of this model.


Authors
-------


Wav2Vec2 XLS-R Adult/Child Indonesian Speech Classifier was trained and evaluated by Ananto Joyoadikusumo. All computation and development are done on Kaggle.


Framework versions
------------------


* Transformers 4.18.0
* Pytorch 1.11.0+cu102
* Datasets 2.2.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #wav2vec2 #audio-classification #generated_from_trainer #id #arxiv-2111.09296 #license-apache-2.0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* 'learning\_rate': 3e-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\_ratio': 0.1
* 'num\_epochs': 4### Training results



Disclaimer
----------


Do consider the biases which came from pre-training datasets that may be carried over into the results of this model.


Authors
-------


Wav2Vec2 XLS-R Adult/Child Indonesian Speech Classifier was trained and evaluated by Ananto Joyoadikusumo. All computation and development are done on Kaggle.


Framework versions
------------------


* Transformers 4.18.0
* Pytorch 1.11.0+cu102
* Datasets 2.2.0
* Tokenizers 0.12.1