
FineTuned wav2vec2 large 960H lv60 self pre-trained facebook model on 72 Hours of MI Diaries Data

WER 13 % -> 9.7% on 20 min test set of MI Diaries audio clips (https://mi-diaries.org/)


### Usage ###
model = Wav2Vec2ForCTC.from_pretrained("caurdy/wav2vec2-large-960h-lv60-self_MIDIARIES_72H_FT")

processor = Wav2Vec2Processor.from_pretrained("caurdy/wav2vec2-large-960h-lv60-self_MIDIARIES_72H_FT")

{"license": "afl-3.0"}
transformers pytorch wav2vec2 automatic-speech-recognition license:afl-3.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #license-afl-3.0 #endpoints_compatible #region-us 


FineTuned wav2vec2 large 960H lv60 self pre-trained facebook model on 72 Hours of MI Diaries Data

WER 13 % -> 9.7% on 20 min test set of MI Diaries audio clips (URL


### Usage ###
model = Wav2Vec2ForCTC.from_pretrained("caurdy/wav2vec2-large-960h-lv60-self_MIDIARIES_72H_FT")

processor = Wav2Vec2Processor.from_pretrained("caurdy/wav2vec2-large-960h-lv60-self_MIDIARIES_72H_FT")

### Usage ###
model = Wav2Vec2ForCTC.from_pretrained("caurdy/wav2vec2-large-960h-lv60-self_MIDIARIES_72H_FT")

processor = Wav2Vec2Processor.from_pretrained("caurdy/wav2vec2-large-960h-lv60-self_MIDIARIES_72H_FT")
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #license-afl-3.0 #endpoints_compatible #region-us 
 ### Usage ###
model = Wav2Vec2ForCTC.from_pretrained("caurdy/wav2vec2-large-960h-lv60-self_MIDIARIES_72H_FT")

processor = Wav2Vec2Processor.from_pretrained("caurdy/wav2vec2-large-960h-lv60-self_MIDIARIES_72H_FT")
passage: TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #license-afl-3.0 #endpoints_compatible #region-us 
### Usage ###
model = Wav2Vec2ForCTC.from_pretrained("caurdy/wav2vec2-large-960h-lv60-self_MIDIARIES_72H_FT")

processor = Wav2Vec2Processor.from_pretrained("caurdy/wav2vec2-large-960h-lv60-self_MIDIARIES_72H_FT")