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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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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_11_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper tiny 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: Common Voice 11.0 |
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type: mozilla-foundation/common_voice_11_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: 41.54533990599564 |
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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: FLEURS |
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type: google/fleurs |
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config: hi_in |
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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: 41.63 |
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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 Hindi |
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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 11.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5538 |
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- Wer: 41.5453 |
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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: 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: 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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:| |
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| 0.7718 | 0.73 | 100 | 0.8130 | 55.6890 | |
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| 0.5169 | 1.47 | 200 | 0.6515 | 48.2517 | |
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| 0.3986 | 2.21 | 300 | 0.6001 | 44.9931 | |
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| 0.3824 | 2.94 | 400 | 0.5720 | 43.5171 | |
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| 0.3328 | 3.67 | 500 | 0.5632 | 42.5112 | |
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| 0.2919 | 4.41 | 600 | 0.5594 | 42.7863 | |
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| 0.2654 | 5.15 | 700 | 0.5552 | 41.6428 | |
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| 0.2618 | 5.88 | 800 | 0.5530 | 41.8893 | |
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| 0.2442 | 6.62 | 900 | 0.5539 | 41.5740 | |
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| 0.238 | 7.35 | 1000 | 0.5538 | 41.5453 | |
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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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