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--- |
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library_name: transformers |
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language: |
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- en |
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license: mit |
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base_model: openai/whisper-large-v3-turbo |
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tags: |
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- generated_from_trainer |
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datasets: |
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- WillHeld/india_accent_cv |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Indian English Acccent |
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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: Indian English Accent |
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type: WillHeld/india_accent_cv |
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args: 'split: train' |
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metrics: |
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- type: wer |
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value: 7.5056000168263415 |
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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 Indian English Acccent |
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This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the Indian English Accent dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2065 |
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- Wer: 7.5056 |
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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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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 5 |
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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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| 0.342 | 0.1943 | 1000 | 0.3226 | 14.1310 | |
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| 0.2741 | 0.3885 | 2000 | 0.3130 | 13.9553 | |
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| 0.2576 | 0.5828 | 3000 | 0.2967 | 12.9931 | |
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| 0.2825 | 0.7770 | 4000 | 0.2692 | 12.3390 | |
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| 0.2295 | 0.9713 | 5000 | 0.2565 | 11.8331 | |
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| 0.1489 | 1.1655 | 6000 | 0.2498 | 11.6933 | |
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| 0.1485 | 1.3598 | 7000 | 0.2452 | 11.1411 | |
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| 0.1385 | 1.5540 | 8000 | 0.2346 | 10.4428 | |
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| 0.1253 | 1.7483 | 9000 | 0.2254 | 10.1852 | |
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| 0.1297 | 1.9425 | 10000 | 0.2144 | 9.7109 | |
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| 0.0594 | 2.1368 | 11000 | 0.2174 | 9.5363 | |
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| 0.0629 | 2.3310 | 12000 | 0.2136 | 9.8276 | |
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| 0.0654 | 2.5253 | 13000 | 0.2102 | 9.4301 | |
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| 0.0625 | 2.7195 | 14000 | 0.2075 | 8.9432 | |
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| 0.0574 | 2.9138 | 15000 | 0.2009 | 8.7802 | |
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| 0.0276 | 3.1080 | 16000 | 0.2050 | 8.4594 | |
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| 0.0251 | 3.3023 | 17000 | 0.2046 | 8.5951 | |
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| 0.0246 | 3.4965 | 18000 | 0.2035 | 8.1187 | |
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| 0.0259 | 3.6908 | 19000 | 0.2002 | 8.0588 | |
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| 0.021 | 3.8850 | 20000 | 0.1951 | 7.9147 | |
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| 0.0072 | 4.0793 | 21000 | 0.2053 | 7.7548 | |
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| 0.0067 | 4.2735 | 22000 | 0.2085 | 7.4972 | |
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| 0.0067 | 4.4678 | 23000 | 0.2094 | 7.6970 | |
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| 0.0062 | 4.6620 | 24000 | 0.2071 | 7.7433 | |
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| 0.0046 | 4.8563 | 25000 | 0.2065 | 7.5056 | |
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### Framework versions |
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- Transformers 4.49.0 |
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- Pytorch 2.2.0a0+81ea7a4 |
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- Datasets 3.3.2 |
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- Tokenizers 0.21.0 |
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