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--- |
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language: |
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- bg |
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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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- hf-asr-leaderboard |
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datasets: |
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- mozilla-foundation/common_voice_11_0 |
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model-index: |
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- name: Whisper Medium Bulgarian |
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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: bg |
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split: test |
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args: bg |
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metrics: |
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- name: Wer |
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type: wer |
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value: 18.7606 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Whisper Medium Bulgarian |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 11.0 dataset. |
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It achieves the following results on the evaluation set: |
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- eval_loss: 0.3423 |
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- eval_wer: 18.7606 |
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- eval_runtime: 1297.1096 |
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- eval_samples_per_second: 1.402 |
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- eval_steps_per_second: 0.044 |
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- epoch: 5.48 |
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- step: 400 |
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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: 16 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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: 50 |
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- training_steps: 1000 |
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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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