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@@ -4,7 +4,6 @@ language:
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  license: apache-2.0
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  tags:
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  - whisper-event
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- - generated_from_trainer
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  datasets:
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  - mozilla-foundation/common_voice_11_0
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  - gigant/romanian_speech_synthesis_0_8_1
@@ -21,9 +20,9 @@ model-index:
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  split: test
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  args: ro
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  metrics:
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- - name: Wer
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- type: wer
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- value: 4.73
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  - task:
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  name: Automatic Speech Recognition
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  type: automatic-speech-recognition
@@ -34,9 +33,11 @@ model-index:
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  split: test
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  args: ro
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  metrics:
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- - name: Wer
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- type: wer
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- value: 19.64
 
 
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  ---
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  # Whisper Medium Romanian
@@ -54,7 +55,7 @@ The architecture is the same as [openai/whisper-medium](https://huggingface.co/o
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  ## Training and evaluation data
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- The model was trained on the Common Voice 11.0 dataset (`train+validation+other splits`) and the Romanian speech synthesis corpus, and was tested on the `test` split of the Common Voice 11.0 dataset.
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  ## Usage
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  Inference with 🤗 Pipeline
@@ -151,4 +152,4 @@ The following hyperparameters were used during training:
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  - Transformers 4.26.0.dev0
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  - Pytorch 1.13.0+cu117
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  - Datasets 2.7.1.dev0
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- - Tokenizers 0.13.2
 
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  license: apache-2.0
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  tags:
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  - whisper-event
 
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  datasets:
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  - mozilla-foundation/common_voice_11_0
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  - gigant/romanian_speech_synthesis_0_8_1
 
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  split: test
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  args: ro
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  metrics:
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+ - name: Wer
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+ type: wer
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+ value: 4.73
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  - task:
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  name: Automatic Speech Recognition
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  type: automatic-speech-recognition
 
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  split: test
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  args: ro
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  metrics:
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+ - name: Wer
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+ type: wer
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+ value: 19.64
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+ metrics:
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+ - wer
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  ---
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  # Whisper Medium Romanian
 
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  ## Training and evaluation data
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+ The model was trained on the Common Voice 11.0 dataset (`train+validation+other` splits) and the Romanian speech synthesis corpus, and was tested on the `test` split of the Common Voice 11.0 dataset.
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  ## Usage
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  Inference with 🤗 Pipeline
 
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  - Transformers 4.26.0.dev0
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  - Pytorch 1.13.0+cu117
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  - Datasets 2.7.1.dev0
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+ - Tokenizers 0.13.2