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--- |
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language: |
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- ml |
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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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- google/fleurs |
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- thennal/IMaSC |
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- thennal/ulca_ml |
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- thennal/msc |
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- thennal/indic_tts_ml |
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metrics: |
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- wer |
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model-index: |
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- name: "Whisper Medium Malayalam - Thennal D K" |
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results: |
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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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dataset: |
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name: Common Voice 11.0 |
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type: mozilla-foundation/common_voice_11_0 |
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config: ml |
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split: test |
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args: ml |
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metrics: |
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- name: Wer |
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type: wer |
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value: 42.98850574712644 |
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- name: Cer |
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type: cer |
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value: 10.390585878818229 |
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--- |
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# Whisper Medium Malayalam - Thennal D K |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on a combined dataset sourced from IMaSC, |
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SMC, Indic TTS, FLEURS (train set), Common Voice 11 (train + other set), OpenSLR, and ULCA. |
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It achieves the following results on the evaluation set (Common Voice 11 test split): |
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- Loss: 0.0730 |
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- WER: 42.9886 |
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- CER: 10.3906 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 4000 |
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- mixed_precision_training: Native AMP |
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### Framework versions |
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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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