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# Wav2Vec2LargeXlsr53-Bangla

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4997
- Wer: 0.4970

## 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: 0.0004
- train_batch_size: 24
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 7.488         | 1.43  | 250  | 3.5201          | 1.0    |
| 2.6655        | 2.85  | 500  | 0.9790          | 0.9119 |
| 0.8826        | 4.28  | 750  | 0.6536          | 0.7847 |
| 0.6013        | 5.71  | 1000 | 0.5361          | 0.7130 |
| 0.4814        | 7.14  | 1250 | 0.5032          | 0.6053 |
| 0.3934        | 8.57  | 1500 | 0.4729          | 0.5827 |
| 0.3394        | 10.0  | 1750 | 0.4785          | 0.6033 |
| 0.2916        | 11.43 | 2000 | 0.4887          | 0.5429 |
| 0.2637        | 12.85 | 2250 | 0.4672          | 0.5287 |
| 0.2299        | 14.28 | 2500 | 0.5027          | 0.5227 |
| 0.2056        | 15.71 | 2750 | 0.5079          | 0.5073 |
| 0.1915        | 17.14 | 3000 | 0.5002          | 0.4987 |
| 0.1772        | 18.57 | 3250 | 0.4930          | 0.5002 |
| 0.1739        | 20.0  | 3500 | 0.4997          | 0.4970 |


### Framework versions

- Transformers 4.24.0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["common_voice_11_0"], "metrics": ["wer"], "model-index": [{"name": "Wav2Vec2LargeXlsr53-Bangla", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "common_voice_11_0", "type": "common_voice_11_0", "config": "bn", "split": "train+validation", "args": "bn"}, "metrics": [{"type": "wer", "value": 0.4969951137937342, "name": "Wer"}]}]}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer dataset:common_voice_11_0 license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice_11_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 

Wav2Vec2LargeXlsr53-Bangla
==========================


This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the common\_voice\_11\_0 dataset.
It achieves the following results on the evaluation set:


* Loss: 0.4997
* Wer: 0.4970


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: 0.0004
* train\_batch\_size: 24
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 48
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 20


### Training results



### Framework versions


* Transformers 4.24.0
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0004
* train\_batch\_size: 24
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 48
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.24.0
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice_11_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0004
* train\_batch\_size: 24
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 48
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.24.0
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice_11_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0004
* train\_batch\_size: 24
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 48
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 20### Training results### Framework versions


* Transformers 4.24.0
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3