--- language: - ms license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - clt013/malay-speech-3k-rows-dataset metrics: - wer model-index: - name: Whisper Small FT Malay - CLT013 results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Malay Speech 3k type: clt013/malay-speech-3k-rows-dataset config: default split: train args: default metrics: - name: Wer type: wer value: 27.169943 --- --- # Whisper Small FT Malay - CLT013 This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Malay Speech 3k dataset. It achieves the following results on the evaluation set: - Loss: 0.545344 - Wer: 27.169943 ## 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 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 1000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.7275 | 0.1 | 100 | 0.677592 | 38.9111 | | 0.521 | 0.2 | 200 | 0.565486 | 36.6151 | | 0.3128 | 0.3 | 300 | 0.525294 | 29.7965 | | 0.2964 | 0.4 | 400 | 0.500519 | 35.2235 | | 0.1631 | 0.5 | 500 | 0.508256 | 36.2845 | | 0.0731 | 0.6 | 600 | 0.532225 | 38.4414 | | 0.0548 | 0.7 | 700 | 0.519905 | 27.2743 | | 0.0289 | 0.8 | 800 | 0.533013 | 27.6917 | | 0.0131 | 0.9 | 900 | 0.548259 | 26.9090 | | 0.0071 | 1.0 | 1000 | 0.545344 | 27.1699 | ### Framework versions - Transformers 4.41.2 - Datasets 2.19.1 - Tokenizers 0.19.1