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# v2-fine-tune-wav2vec2-Vietnamese-ARS-demo

This model is a fine-tuned version of [nguyenvulebinh/wav2vec2-base-vietnamese-250h](https://huggingface.co/nguyenvulebinh/wav2vec2-base-vietnamese-250h) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2515
- Wer: 0.2235

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 8.8651        | 0.34  | 500  | 3.6919          | 0.9999 |
| 3.54          | 0.69  | 1000 | 3.3584          | 1.0    |
| 2.9478        | 1.03  | 1500 | 2.2535          | 0.9885 |
| 1.9147        | 1.37  | 2000 | 0.9977          | 0.7260 |
| 1.1667        | 1.71  | 2500 | 0.5577          | 0.4746 |
| 0.844         | 2.06  | 3000 | 0.4129          | 0.3581 |
| 0.6968        | 2.4   | 3500 | 0.3566          | 0.3090 |
| 0.6273        | 2.74  | 4000 | 0.3243          | 0.2813 |
| 0.5434        | 3.09  | 4500 | 0.3076          | 0.2631 |
| 0.5069        | 3.43  | 5000 | 0.2902          | 0.2539 |
| 0.4842        | 3.77  | 5500 | 0.2752          | 0.2432 |
| 0.4318        | 4.12  | 6000 | 0.2854          | 0.2384 |
| 0.3951        | 4.46  | 6500 | 0.2674          | 0.2350 |
| 0.3954        | 4.8   | 7000 | 0.2628          | 0.2322 |
| 0.3763        | 5.14  | 7500 | 0.2609          | 0.2284 |
| 0.3652        | 5.49  | 8000 | 0.2508          | 0.2249 |
| 0.3703        | 5.83  | 8500 | 0.2515          | 0.2235 |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.12.0+cu113
- Datasets 1.18.3
- Tokenizers 0.12.1

{"license": "cc-by-nc-4.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "v2-fine-tune-wav2vec2-Vietnamese-ARS-demo", "results": []}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer license:cc-by-nc-4.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-cc-by-nc-4.0 #endpoints_compatible #region-us 

v2-fine-tune-wav2vec2-Vietnamese-ARS-demo
=========================================


This model is a fine-tuned version of nguyenvulebinh/wav2vec2-base-vietnamese-250h on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2515
* Wer: 0.2235


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: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 6
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.17.0
* Pytorch 1.12.0+cu113
* Datasets 1.18.3
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 6
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.12.0+cu113
* Datasets 1.18.3
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-cc-by-nc-4.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 6
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.12.0+cu113
* Datasets 1.18.3
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-cc-by-nc-4.0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 6
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.17.0
* Pytorch 1.12.0+cu113
* Datasets 1.18.3
* Tokenizers 0.12.1