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--- |
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language: |
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- km |
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license: apache-2.0 |
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tags: |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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datasets: |
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- openslr |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small Km - Kak Soky |
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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: SLR42 |
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type: openslr |
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args: 'config: km, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 35.665399239543724 |
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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 Km - Kak Soky |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the SLR42 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1471 |
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- Wer: 35.6654 |
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## Model description |
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The model was fine-tuned on both encoder-decoder of transformer-based. |
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## Intended uses & limitations |
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The training data is limited, thus the performance is also limited to only reading speech and a limited domain (tourism). |
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## Training and evaluation data |
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The training and evaluation data was split in a 9:1 ratio from Google Text-to-speech corpus. |
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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: 2 |
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- eval_batch_size: 4 |
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- seed: 42 |
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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: 4000 |
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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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| 0.3639 | 0.76 | 1000 | 0.3452 | 71.9392 | |
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| 0.1553 | 1.53 | 2000 | 0.2025 | 49.0494 | |
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| 0.0565 | 2.29 | 3000 | 0.1664 | 39.9240 | |
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| 0.0334 | 3.06 | 4000 | 0.1471 | 35.6654 | |
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### Framework versions |
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- Transformers 4.25.0.dev0 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.7.0 |
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- Tokenizers 0.13.2 |
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