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--- |
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license: apache-2.0 |
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base_model: openai/whisper-tiny |
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tags: |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_16_0 |
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language: |
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- hu |
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widget: |
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- example_title: Sample 1 |
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src: https://huggingface.co/datasets/Hungarians/samples/resolve/main/Sample1.flac |
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- example_title: Sample 2 |
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src: https://huggingface.co/datasets/Hungarians/samples/resolve/main/Sample2.flac |
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metrics: |
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- wer |
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pipeline_tag: automatic-speech-recognition |
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model-index: |
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- name: Whisper Tiny Hu v3 |
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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 16.0 - Hungarian |
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type: mozilla-foundation/common_voice_16_0 |
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config: hu |
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split: test |
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args: hu |
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metrics: |
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- name: Wer |
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type: wer |
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value: 12.7928 |
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verified: true |
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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 Tiny Hu v3 |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 16.0 dataset. |
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It achieves the following results on the evaluation set: |
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- eval_loss: 0.2041 |
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- eval_wer_ortho: 13.8474 |
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- eval_wer: 12.7928 |
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- eval_runtime: 1002.1306 |
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- eval_samples_per_second: 4.621 |
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- eval_steps_per_second: 0.578 |
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- epoch: 13.39 |
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- step: 20000 |
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## Model description |
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Hungarian language trained modell. Faster-whisper versions in int8, fp16 and ft32 floders. |
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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: 4e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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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: constant_with_warmup |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 20000 |
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- mixed_precision_training: Native AMP |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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