Whisper Small Ablation Add NLD 80

--- base_model: openai/whisper-small datasets: - fleurs library_name: transformers license: apache-2.0 metrics: - wer tags: - generated_from_trainer model-index: - name: whisper-small-ablation-add-NLD-80 results: - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: fleurs type: fleurs config: id_id split: None args: id_id metrics: - type: wer value: 17.020648967551622 name: Wer --- # whisper-small-ablation-add-NLD-80 This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the fleurs dataset. It achieves the following results on the evaluation set: - Loss: 0.4274 - Wer: 17.0206 ## 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: 32 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 1000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:-------:| | 0.3531 | 0.4673 | 200 | 0.4262 | 18.9012 | | 0.2799 | 0.9346 | 400 | 0.4623 | 18.4440 | | 0.1829 | 1.4019 | 600 | 0.4345 | 18.7094 | | 0.1841 | 1.8692 | 800 | 0.4215 | 17.1976 | | 0.091 | 2.3364 | 1000 | 0.4274 | 17.0206 | ### Framework versions - Transformers 4.45.0 - Pytorch 2.11.0+cu130 - Datasets 3.0.1 - Tokenizers 0.20.0