
# XLS-R-300m-FTSpeech

## Model description

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the [FTSpeech dataset](https://ftspeech.github.io/), being a dataset of 1,800 hours of transcribed speeches from the Danish parliament.


## Performance

The model achieves the following WER scores (lower is better):

| **Dataset** | **WER without LM** | **WER with 5-gram LM** |
| :---:   | ---: | ---: |
| [Danish part of Common Voice 8.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0/viewer/da/train) | 20.48 | 17.91 |
| [Alvenir test set](https://huggingface.co/datasets/Alvenir/alvenir_asr_da_eval) | 15.46 | 13.84 |


## License

The use of this model needs to adhere to [this license from the Danish Parliament](https://www.ft.dk/da/aktuelt/tv-fra-folketinget/deling-og-rettigheder).
{"language": ["da"], "license": "other", "datasets": ["ftspeech"], "metrics": ["wer"], "tasks": ["automatic-speech-recognition"], "base_model": "facebook/wav2vec2-xls-r-300m", "model-index": [{"name": "wav2vec2-xls-r-300m-ftspeech", "results": [{"task": {"type": "automatic-speech-recognition"}, "dataset": {"name": "Danish Common Voice 8.0", "type": "mozilla-foundation/common_voice_8_0", "args": "da"}, "metrics": [{"type": "wer", "value": 17.91}]}, {"task": {"type": "automatic-speech-recognition"}, "dataset": {"name": "Alvenir ASR test dataset", "type": "Alvenir/alvenir_asr_da_eval"}, "metrics": [{"type": "wer", "value": 13.84}]}]}]}
transformers pytorch safetensors wav2vec2 automatic-speech-recognition da dataset:ftspeech base_model:facebook/wav2vec2-xls-r-300m license:other model-index endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #safetensors #wav2vec2 #automatic-speech-recognition #da #dataset-ftspeech #base_model-facebook/wav2vec2-xls-r-300m #license-other #model-index #endpoints_compatible #has_space #region-us 

XLS-R-300m-FTSpeech
===================


Model description
-----------------


This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the FTSpeech dataset, being a dataset of 1,800 hours of transcribed speeches from the Danish parliament.


## Performance


The model achieves the following WER scores (lower is better):



License
-------


The use of this model needs to adhere to this license from the Danish Parliament.



TAGS
#transformers #pytorch #safetensors #wav2vec2 #automatic-speech-recognition #da #dataset-ftspeech #base_model-facebook/wav2vec2-xls-r-300m #license-other #model-index #endpoints_compatible #has_space #region-us 

passage: TAGS
#transformers #pytorch #safetensors #wav2vec2 #automatic-speech-recognition #da #dataset-ftspeech #base_model-facebook/wav2vec2-xls-r-300m #license-other #model-index #endpoints_compatible #has_space #region-us 
