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--- |
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language: |
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- hi |
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license: apache-2.0 |
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base_model: openai/whisper-base |
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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_16_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Base Hindi |
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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_0 hi |
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type: mozilla-foundation/common_voice_16_0 |
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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: 28.648953267516852 |
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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 Base Hindi |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_16_0 hi dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4679 |
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- Wer: 28.6490 |
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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-06 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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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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| 0.6425 | 6.01 | 500 | 0.7025 | 41.4477 | |
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| 0.3973 | 13.0 | 1000 | 0.5367 | 33.9692 | |
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| 0.3125 | 19.01 | 1500 | 0.4927 | 31.4458 | |
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| 0.2848 | 26.0 | 2000 | 0.4739 | 30.1037 | |
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| 0.2201 | 32.01 | 2500 | 0.4675 | 29.4859 | |
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| 0.2257 | 39.01 | 3000 | 0.4637 | 28.9933 | |
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| 0.1837 | 46.0 | 3500 | 0.4657 | 28.9140 | |
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| 0.1897 | 52.01 | 4000 | 0.4658 | 28.7450 | |
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| 0.1764 | 59.0 | 4500 | 0.4676 | 28.7178 | |
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| 0.1681 | 65.01 | 5000 | 0.4679 | 28.6490 | |
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### Framework versions |
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- Transformers 4.37.0.dev0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.2.dev0 |
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- Tokenizers 0.15.0 |
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