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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: 27.434200914195074 |
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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: 0.4926 |
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- Wer: 27.4342 |
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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: 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: 2000 |
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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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| 0.563 | 2.02 | 200 | 0.6270 | 38.2146 | |
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| 0.3107 | 5.01 | 400 | 0.4695 | 30.0641 | |
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| 0.1535 | 7.03 | 600 | 0.4548 | 27.7139 | |
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| 0.0841 | 10.02 | 800 | 0.4926 | 27.4342 | |
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| 0.0357 | 13.01 | 1000 | 0.5585 | 28.1772 | |
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| 0.0152 | 15.03 | 1200 | 0.6247 | 28.0687 | |
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| 0.0063 | 18.02 | 1400 | 0.6796 | 28.1856 | |
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| 0.0036 | 21.0 | 1600 | 0.7097 | 28.2670 | |
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| 0.0029 | 23.03 | 1800 | 0.7270 | 28.1960 | |
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| 0.0024 | 26.01 | 2000 | 0.7336 | 28.2649 | |
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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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