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# wav2vec2-xls-r-300m-lg

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the COMMON_VOICE - LG dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6989
- Wer: 0.8529

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.9089        | 6.33  | 500  | 2.8983          | 1.0002 |
| 2.5754        | 12.66 | 1000 | 1.8710          | 1.0    |
| 1.4093        | 18.99 | 1500 | 0.7195          | 0.8547 |


### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0

#### Evaluation Commands
1. To evaluate on `mozilla-foundation/common_voice_7_0` with split `test`

```bash
python eval.py --model_id samitizerxu/wav2vec2-xls-r-300m-lg --dataset mozilla-foundation/common_voice_7_0 --config lg --split test
```

{"language": ["lg"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "robust-speech-event", "common_voice", "lg", "generated_from_trainer", "hf-asr-leaderboard"], "datasets": ["common_voice"], "model-index": [{"name": "wav2vec2-xls-r-300m-lg", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Common Voice 7", "type": "mozilla-foundation/common_voice_7_0", "args": "sv-SE"}, "metrics": [{"type": "wer", "value": 78.89, "name": "Test WER"}, {"type": "cer", "value": 15.16, "name": "Test CER"}]}]}]}
transformers pytorch wav2vec2 automatic-speech-recognition robust-speech-event common_voice lg generated_from_trainer hf-asr-leaderboard dataset:common_voice license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #robust-speech-event #common_voice #lg #generated_from_trainer #hf-asr-leaderboard #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us 

wav2vec2-xls-r-300m-lg
======================


This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the COMMON\_VOICE - LG dataset.
It achieves the following results on the evaluation set:


* Loss: 0.6989
* Wer: 0.8529


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: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20.0
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.2.dev0
* Tokenizers 0.11.0


#### Evaluation Commands


1. To evaluate on 'mozilla-foundation/common\_voice\_7\_0' with split 'test'



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.2.dev0
* Tokenizers 0.11.0 #### Evaluation Commands


1. To evaluate on 'mozilla-foundation/common\_voice\_7\_0' with split 'test'
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #robust-speech-event #common_voice #lg #generated_from_trainer #hf-asr-leaderboard #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.2.dev0
* Tokenizers 0.11.0 #### Evaluation Commands


1. To evaluate on 'mozilla-foundation/common\_voice\_7\_0' with split 'test'
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #robust-speech-event #common_voice #lg #generated_from_trainer #hf-asr-leaderboard #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20.0
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.17.0.dev0
* Pytorch 1.10.2+cu102
* Datasets 1.18.2.dev0
* Tokenizers 0.11.0#### Evaluation Commands


1. To evaluate on 'mozilla-foundation/common\_voice\_7\_0' with split 'test'