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--- |
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language: |
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- ta |
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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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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small Tamil |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: google/fleurs |
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type: google/fleurs |
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config: ta_in |
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split: test |
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metrics: |
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- type: wer |
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value: 15.8 |
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name: WER |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: mozilla-foundation/common_voice_11_0 |
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type: mozilla-foundation/common_voice_11_0 |
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config: ta |
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split: test |
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metrics: |
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- type: wer |
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value: 11.15 |
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name: WER |
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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 Ta - Bharat Ramanathan (Kudos to him for developing it) |
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# This is a copy of his model for academic purpose. |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1803 |
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- Wer: 17.1456 |
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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: 16 |
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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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| 0.3374 | 0.1 | 500 | 0.2579 | 23.3804 | |
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| 0.29 | 0.2 | 1000 | 0.2260 | 20.9937 | |
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| 0.2522 | 0.3 | 1500 | 0.2139 | 20.0682 | |
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| 0.2338 | 0.4 | 2000 | 0.2025 | 19.6785 | |
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| 0.223 | 0.5 | 2500 | 0.1979 | 18.3147 | |
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| 0.211 | 0.6 | 3000 | 0.1927 | 17.8276 | |
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| 0.2032 | 0.7 | 3500 | 0.1865 | 17.3892 | |
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| 0.1978 | 0.8 | 4000 | 0.1839 | 17.5353 | |
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| 0.1972 | 0.9 | 4500 | 0.1812 | 17.0969 | |
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| 0.1894 | 1.0 | 5000 | 0.1803 | 17.1456 | |
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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 |
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- Tokenizers 0.13.2 |
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