
# DistilWav2Vec2 Adult/Child Indonesian Speech Classifier 52M

DistilWav2Vec2 Adult/Child Indonesian Speech Classifier is an audio classification model based on the [wav2vec 2.0](https://arxiv.org/abs/2006.11477) architecture. This model is a distilled version of [wav2vec2-adult-child-id-cls](https://huggingface.co/bookbot/wav2vec2-adult-child-id-cls) 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)                      |
| ---------------------------------------- | ------- | ----------- | ---------------------------------------------------- |
| `distil-wav2vec2-adult-child-id-cls-52m` | 52m     | wav2vec 2.0 | 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 | 0.1560 | 94.89%   | 0.9480 |

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:

-   `learning_rate`: 3e-05
-   `train_batch_size`: 32
-   `eval_batch_size`: 32
-   `seed`: 42
-   `gradient_accumulation_steps`: 4
-   `total_train_batch_size`: 128
-   `optimizer`: Adam with `betas=(0.9,0.999)` and `epsilon=1e-08`
-   `lr_scheduler_type`: linear
-   `lr_scheduler_warmup_ratio`: 0.1
-   `num_epochs`: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |   F1   |
| :-----------: | :---: | :--: | :-------------: | :------: | :----: |
|    0.2494     |  1.0  |  76  |     0.1706      |  0.9454  | 0.9421 |
|    0.2015     |  2.0  | 152  |     0.1519      |  0.9483  | 0.9464 |
|    0.1674     |  3.0  | 228  |     0.1560      |  0.9489  | 0.9480 |
|    0.1596     |  4.0  | 304  |     0.1760      |  0.9449  | 0.9414 |
|    0.0873     |  5.0  | 380  |     0.1825      |  0.9478  | 0.9452 |
|    0.0996     |  6.0  | 456  |     0.1733      |  0.9478  | 0.9460 |
|    0.1055     |  7.0  | 532  |     0.1749      |  0.9454  | 0.9433 |

## Disclaimer

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

## Authors

DistilWav2Vec2 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 4.16.2
-   Pytorch 1.10.2+cu102
-   Datasets 1.18.3
-   Tokenizers 0.10.3

{"language": "id", "license": "apache-2.0", "tags": ["audio-classification", "generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "distil-wav2vec2-adult-child-id-cls-52m", "results": []}]}
transformers pytorch tensorboard wav2vec2 audio-classification generated_from_trainer id arxiv:2006.11477 license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #audio-classification #generated_from_trainer #id #arxiv-2006.11477 #license-apache-2.0 #endpoints_compatible #region-us 

DistilWav2Vec2 Adult/Child Indonesian Speech Classifier 52M
===========================================================


DistilWav2Vec2 Adult/Child Indonesian Speech Classifier is an audio classification model based on the wav2vec 2.0 architecture. This model is a distilled version of wav2vec2-adult-child-id-cls 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': 32
* 'eval\_batch\_size': 32
* 'seed': 42
* 'gradient\_accumulation\_steps': 4
* 'total\_train\_batch\_size': 128
* 'optimizer': Adam with 'betas=(0.9,0.999)' and 'epsilon=1e-08'
* 'lr\_scheduler\_type': linear
* 'lr\_scheduler\_warmup\_ratio': 0.1
* 'num\_epochs': 7


### 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
-------


DistilWav2Vec2 Adult/Child Indonesian Speech Classifier was trained and evaluated by Ananto Joyoadikusumo. All computation and development are done on Kaggle.


### Framework versions


* Transformers 4.16.2
* Pytorch 1.10.2+cu102
* Datasets 1.18.3
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* 'learning\_rate': 3e-05
* 'train\_batch\_size': 32
* 'eval\_batch\_size': 32
* 'seed': 42
* 'gradient\_accumulation\_steps': 4
* 'total\_train\_batch\_size': 128
* 'optimizer': Adam with 'betas=(0.9,0.999)' and 'epsilon=1e-08'
* 'lr\_scheduler\_type': linear
* 'lr\_scheduler\_warmup\_ratio': 0.1
* 'num\_epochs': 7 ### 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
-------


DistilWav2Vec2 Adult/Child Indonesian Speech Classifier was trained and evaluated by Ananto Joyoadikusumo. All computation and development are done on Kaggle. ### Framework versions


* Transformers 4.16.2
* Pytorch 1.10.2+cu102
* Datasets 1.18.3
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #audio-classification #generated_from_trainer #id #arxiv-2006.11477 #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* 'learning\_rate': 3e-05
* 'train\_batch\_size': 32
* 'eval\_batch\_size': 32
* 'seed': 42
* 'gradient\_accumulation\_steps': 4
* 'total\_train\_batch\_size': 128
* 'optimizer': Adam with 'betas=(0.9,0.999)' and 'epsilon=1e-08'
* 'lr\_scheduler\_type': linear
* 'lr\_scheduler\_warmup\_ratio': 0.1
* 'num\_epochs': 7 ### 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
-------


DistilWav2Vec2 Adult/Child Indonesian Speech Classifier was trained and evaluated by Ananto Joyoadikusumo. All computation and development are done on Kaggle. ### Framework versions


* Transformers 4.16.2
* Pytorch 1.10.2+cu102
* Datasets 1.18.3
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #wav2vec2 #audio-classification #generated_from_trainer #id #arxiv-2006.11477 #license-apache-2.0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* 'learning\_rate': 3e-05
* 'train\_batch\_size': 32
* 'eval\_batch\_size': 32
* 'seed': 42
* 'gradient\_accumulation\_steps': 4
* 'total\_train\_batch\_size': 128
* 'optimizer': Adam with 'betas=(0.9,0.999)' and 'epsilon=1e-08'
* 'lr\_scheduler\_type': linear
* 'lr\_scheduler\_warmup\_ratio': 0.1
* 'num\_epochs': 7### 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
-------


DistilWav2Vec2 Adult/Child Indonesian Speech Classifier was trained and evaluated by Ananto Joyoadikusumo. All computation and development are done on Kaggle.### Framework versions


* Transformers 4.16.2
* Pytorch 1.10.2+cu102
* Datasets 1.18.3
* Tokenizers 0.10.3