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# wav2vec2-large-xls-r-300m-cv8-nl

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 dataset. In addition a 6gram KenLM model was trained and used. The KenLM model was based on train+validation Common Voice 8
It achieves results depicted on the rigth side on the model card (testset CV8)

## Model description

Dutch wav2vec2-xls-r-300m model using Common Voice 8 dataset

## Intended uses & limitations

More information needed

## Training and evaluation data

The model was trained on Dutch common voice 8 with 75 epochs. The train set consisted of the common voice 8 train set and evaluation set was the common voice 8 validation set. The WER reported is on the common voice 8 test set which was not part of training nor validation (eval)

## Training procedure

### Training hyperparameters

### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.18.1
- Tokenizers 0.11.0

{"language": ["nl"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "nl", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-cv8-nl", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Common Voice 8", "type": "mozilla-foundation/common_voice_8_0", "args": "nl"}, "metrics": [{"type": "wer", "value": 14.53, "name": "Test WER"}, {"type": "cer", "value": 4.7, "name": "Test CER"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Robust Speech Event - Dev Data", "type": "speech-recognition-community-v2/dev_data", "args": "nl"}, "metrics": [{"type": "wer", "value": 33.7, "name": "Test WER"}, {"type": "cer", "value": 15.64, "name": "Test CER"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Robust Speech Event - Test Data", "type": "speech-recognition-community-v2/eval_data", "args": "nl"}, "metrics": [{"type": "wer", "value": 35.19, "name": "Test WER"}]}]}]}
transformers pytorch wav2vec2 automatic-speech-recognition mozilla-foundation/common_voice_8_0 generated_from_trainer nl robust-speech-event model_for_talk hf-asr-leaderboard dataset:mozilla-foundation/common_voice_8_0 license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #nl #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 




# wav2vec2-large-xls-r-300m-cv8-nl

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. In addition a 6gram KenLM model was trained and used. The KenLM model was based on train+validation Common Voice 8
It achieves results depicted on the rigth side on the model card (testset CV8)

## Model description

Dutch wav2vec2-xls-r-300m model using Common Voice 8 dataset

## Intended uses & limitations

More information needed

## Training and evaluation data

The model was trained on Dutch common voice 8 with 75 epochs. The train set consisted of the common voice 8 train set and evaluation set was the common voice 8 validation set. The WER reported is on the common voice 8 test set which was not part of training nor validation (eval)

## Training procedure

### Training hyperparameters

### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.18.1
- Tokenizers 0.11.0

# wav2vec2-large-xls-r-300m-cv8-nl

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. In addition a 6gram KenLM model was trained and used. The KenLM model was based on train+validation Common Voice 8
It achieves results depicted on the rigth side on the model card (testset CV8) ## Model description

Dutch wav2vec2-xls-r-300m model using Common Voice 8 dataset ## Intended uses & limitations

More information needed ## Training and evaluation data

The model was trained on Dutch common voice 8 with 75 epochs. The train set consisted of the common voice 8 train set and evaluation set was the common voice 8 validation set. The WER reported is on the common voice 8 test set which was not part of training nor validation (eval) ## Training procedure ### Training hyperparameters ### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.18.1
- Tokenizers 0.11.0
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #nl #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
 # wav2vec2-large-xls-r-300m-cv8-nl

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. In addition a 6gram KenLM model was trained and used. The KenLM model was based on train+validation Common Voice 8
It achieves results depicted on the rigth side on the model card (testset CV8) ## Model description

Dutch wav2vec2-xls-r-300m model using Common Voice 8 dataset ## Intended uses & limitations

More information needed ## Training and evaluation data

The model was trained on Dutch common voice 8 with 75 epochs. The train set consisted of the common voice 8 train set and evaluation set was the common voice 8 validation set. The WER reported is on the common voice 8 test set which was not part of training nor validation (eval) ## Training procedure ### Training hyperparameters ### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.18.1
- Tokenizers 0.11.0
passage: TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #nl #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
# wav2vec2-large-xls-r-300m-cv8-nl

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. In addition a 6gram KenLM model was trained and used. The KenLM model was based on train+validation Common Voice 8
It achieves results depicted on the rigth side on the model card (testset CV8)## Model description

Dutch wav2vec2-xls-r-300m model using Common Voice 8 dataset## Intended uses & limitations

More information needed## Training and evaluation data

The model was trained on Dutch common voice 8 with 75 epochs. The train set consisted of the common voice 8 train set and evaluation set was the common voice 8 validation set. The WER reported is on the common voice 8 test set which was not part of training nor validation (eval)## Training procedure### Training hyperparameters### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.18.1
- Tokenizers 0.11.0