# sammy786/wav2vec2-xlsr-breton

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - br dataset.

## Model description
"facebook/wav2vec2-xls-r-1b" was finetuned.

## Intended uses & limitations
More information needed
## Training and evaluation data
Training data - 
Common voice Finnish train.tsv, dev.tsv and other.tsv

## Training procedure
For creating the train dataset, all possible datasets were appended and 90-10 split was used. 

### Training hyperparameters

The following hyperparameters were used during training:

- learning_rate: 0.000045637994662983496
- train_batch_size: 8
- eval_batch_size: 32
- seed: 13
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP



### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.0+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.10.3

#### Evaluation Commands

1. To evaluate on `mozilla-foundation/common_voice_8_0` with split `test`

```bash
python eval.py --model_id sammy786/wav2vec2-xlsr-breton --dataset mozilla-foundation/common_voice_8_0 --config br --split test
```
{"language": ["br"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "br", "generated_from_trainer", "hf-asr-leaderboard", "model_for_talk", "mozilla-foundation/common_voice_8_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "sammy786/wav2vec2-xlsr-breton", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Common Voice 8", "type": "mozilla-foundation/common_voice_8_0", "args": "br"}, "metrics": [{"type": "wer", "value": 48.2, "name": "Test WER"}, {"type": "cer", "value": 15.02, "name": "Test CER"}]}]}]}
transformers pytorch wav2vec2 automatic-speech-recognition br generated_from_trainer hf-asr-leaderboard model_for_talk mozilla-foundation/common_voice_8_0 robust-speech-event dataset:mozilla-foundation/common_voice_8_0 license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #br #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 

# sammy786/wav2vec2-xlsr-breton

This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - br dataset.

## Model description
"facebook/wav2vec2-xls-r-1b" was finetuned.

## Intended uses & limitations
More information needed
## Training and evaluation data
Training data - 
Common voice Finnish URL, URL and URL

## Training procedure
For creating the train dataset, all possible datasets were appended and 90-10 split was used. 

### Training hyperparameters

The following hyperparameters were used during training:

- learning_rate: 0.000045637994662983496
- train_batch_size: 8
- eval_batch_size: 32
- seed: 13
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP



### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.0+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.10.3

#### Evaluation Commands

1. To evaluate on 'mozilla-foundation/common_voice_8_0' with split 'test'


# sammy786/wav2vec2-xlsr-breton

This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - br dataset. ## Model description
"facebook/wav2vec2-xls-r-1b" was finetuned. ## Intended uses & limitations
More information needed ## Training and evaluation data
Training data - 
Common voice Finnish URL, URL and URL ## Training procedure
For creating the train dataset, all possible datasets were appended and 90-10 split was used. ### Training hyperparameters

The following hyperparameters were used during training:

- learning_rate: 0.000045637994662983496
- train_batch_size: 8
- eval_batch_size: 32
- seed: 13
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP ### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.0+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.10.3 #### Evaluation Commands

1. To evaluate on 'mozilla-foundation/common_voice_8_0' with split 'test'
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #br #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
 # sammy786/wav2vec2-xlsr-breton

This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - br dataset. ## Model description
"facebook/wav2vec2-xls-r-1b" was finetuned. ## Intended uses & limitations
More information needed ## Training and evaluation data
Training data - 
Common voice Finnish URL, URL and URL ## Training procedure
For creating the train dataset, all possible datasets were appended and 90-10 split was used. ### Training hyperparameters

The following hyperparameters were used during training:

- learning_rate: 0.000045637994662983496
- train_batch_size: 8
- eval_batch_size: 32
- seed: 13
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP ### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.0+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.10.3 #### Evaluation Commands

1. To evaluate on 'mozilla-foundation/common_voice_8_0' with split 'test'
passage: TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #br #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
# sammy786/wav2vec2-xlsr-breton

This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - br dataset.## Model description
"facebook/wav2vec2-xls-r-1b" was finetuned.## Intended uses & limitations
More information needed## Training and evaluation data
Training data - 
Common voice Finnish URL, URL and URL## Training procedure
For creating the train dataset, all possible datasets were appended and 90-10 split was used.### Training hyperparameters

The following hyperparameters were used during training:

- learning_rate: 0.000045637994662983496
- train_batch_size: 8
- eval_batch_size: 32
- seed: 13
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.0+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.10.3#### Evaluation Commands

1. To evaluate on 'mozilla-foundation/common_voice_8_0' with split 'test'