| --- |
| language: |
| - en |
| license: apache-2.0 |
| base_model: openai/whisper-small |
| tags: |
| - generated_from_trainer |
| datasets: |
| - rngzhi/cs3264-project |
| metrics: |
| - wer |
| model-index: |
| - name: Whisper Small - Singlish v2 |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: rngzhi/cs3264-project |
| type: rngzhi/cs3264-project |
| metrics: |
| - name: Wer |
| type: wer |
| value: 4.923638021426943 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # Whisper Small - Singlish v2 |
|
|
| This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the rngzhi/cs3264-project dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1850 |
| - Wer: 4.9236 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 1e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 32 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 25 |
| - training_steps: 800 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:------:|:----:|:---------------:|:------:| |
| | 0.5404 | 0.0625 | 50 | 0.1970 | 5.6075 | |
| | 0.075 | 1.0144 | 100 | 0.1557 | 4.8780 | |
| | 0.042 | 1.0769 | 150 | 0.1610 | 4.9692 | |
| | 0.0185 | 2.0288 | 200 | 0.1628 | 4.9122 | |
| | 0.0117 | 2.0913 | 250 | 0.1651 | 5.0262 | |
| | 0.0096 | 3.0431 | 300 | 0.1716 | 5.0490 | |
| | 0.007 | 3.1056 | 350 | 0.1747 | 5.0034 | |
| | 0.0045 | 4.0575 | 400 | 0.1783 | 5.1402 | |
| | 0.0046 | 5.0094 | 450 | 0.1749 | 5.1288 | |
| | 0.004 | 5.0719 | 500 | 0.1782 | 5.0148 | |
| | 0.0021 | 6.0237 | 550 | 0.1814 | 5.0034 | |
| | 0.004 | 6.0862 | 600 | 0.1813 | 4.9920 | |
| | 0.0024 | 7.0381 | 650 | 0.1844 | 4.9350 | |
| | 0.0022 | 7.1006 | 700 | 0.1834 | 4.9008 | |
| | 0.0032 | 8.0525 | 750 | 0.1850 | 4.9236 | |
| | 0.0016 | 9.0044 | 800 | 0.1850 | 4.9236 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.40.0.dev0 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.18.1.dev0 |
| - Tokenizers 0.19.1 |
|
|
