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update model card README.md
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README.md
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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 1000 steps - Shripad Bhat
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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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---
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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 1000 steps - Shripad Bhat
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) 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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