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--- |
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license: mit |
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base_model: distil-whisper/distil-large-v3 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_16_1 |
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metrics: |
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- wer |
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model-index: |
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- name: distil-whisper/distil-large-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: mozilla-foundation/common_voice_16_1 hi |
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type: mozilla-foundation/common_voice_16_1 |
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config: hi |
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split: test |
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args: hi |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.26639882562002626 |
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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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# distil-whisper/distil-large-v3 |
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This model is a fine-tuned version of [distil-whisper/distil-large-v3](https://huggingface.co/distil-whisper/distil-large-v3) on the mozilla-foundation/common_voice_16_1 hi dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3749 |
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- Wer: 0.2664 |
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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: 0.0001 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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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: 5000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 0.1035 | 4.5 | 1000 | 0.3015 | 0.3250 | |
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| 0.0165 | 9.01 | 2000 | 0.3496 | 0.3007 | |
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| 0.0022 | 13.51 | 3000 | 0.3649 | 0.2786 | |
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| 0.0011 | 18.02 | 4000 | 0.3700 | 0.2681 | |
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| 0.0003 | 22.52 | 5000 | 0.3749 | 0.2664 | |
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### Framework versions |
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- Transformers 4.40.0.dev0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.1 |
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