--- license: apache-2.0 base_model: openai/whisper-medium tags: - generated_from_trainer datasets: - Ussen/swc-drc-katanga metrics: - wer model-index: - name: whisper-tiny-swc-drc-kat-2 results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Ussen/swc-drc-katanga type: Ussen/swc-drc-katanga config: default split: train args: default metrics: - name: Wer type: wer value: 0.39136057941024316 --- # whisper-tiny-swc-drc-kat-2 This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Ussen/swc-drc-katanga dataset. It achieves the following results on the evaluation set: - Loss: 0.8770 - Wer Ortho: 39.7101 - Wer: 0.3914 ## 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: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 8 - total_train_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: constant_with_warmup - lr_scheduler_warmup_steps: 500 - training_steps: 4000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:| | 0.3735 | 2.96 | 1000 | 0.6459 | 48.5374 | 0.4783 | | 0.081 | 5.93 | 2000 | 0.7478 | 38.5969 | 0.3797 | | 0.0279 | 8.89 | 3000 | 0.8653 | 38.7523 | 0.3813 | | 0.0189 | 11.85 | 4000 | 0.8770 | 39.7101 | 0.3914 | ### Framework versions - Transformers 4.33.0.dev0 - Pytorch 1.13.1+cu117 - Datasets 2.13.1 - Tokenizers 0.12.1