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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 Small Hindi - 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: 21.451908746990714
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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 Small Hindi - 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: 0.3909
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- Wer: 21.4519
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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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| 0.4337 | 0.73 | 100 | 0.4874 | 47.5868 |
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| 0.1894 | 1.47 | 200 | 0.3264 | 23.9482 |
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| 0.1007 | 2.21 | 300 | 0.3101 | 22.5267 |
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| 0.0984 | 2.94 | 400 | 0.3064 | 21.5723 |
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| 0.0555 | 3.67 | 500 | 0.3325 | 22.0251 |
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| 0.029 | 4.41 | 600 | 0.3439 | 21.4863 |
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| 0.0163 | 5.15 | 700 | 0.3668 | 21.6468 |
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| 0.0153 | 5.88 | 800 | 0.3756 | 21.4662 |
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| 0.0081 | 6.62 | 900 | 0.3888 | 21.5035 |
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| 0.0059 | 7.35 | 1000 | 0.3909 | 21.4519 |
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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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