--- library_name: peft license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer metrics: - wer - cer model-index: - name: whisper-model-small-ro-finetune-5k-00-00 results: [] datasets: - victors3136/dataset-5k-00it-00sp language: - ro --- # whisper-model-small-ro-finetune-5k-00-00 This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.1231 - Wer: 0.9108 - Cer: 0.9394 ## 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: 2e-05 - train_batch_size: 32 - eval_batch_size: 16 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 64 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 30 - num_epochs: 5 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:| | 3.4209 | 1.0 | 63 | 2.2366 | 0.5657 | 0.2664 | | 1.8723 | 2.0 | 126 | 1.2667 | 1.0727 | 1.1125 | | 1.2238 | 3.0 | 189 | 1.1675 | 0.9135 | 0.9796 | | 1.0924 | 4.0 | 252 | 1.1347 | 0.8912 | 0.9512 | | 1.0608 | 5.0 | 315 | 1.1231 | 0.9108 | 0.9394 | ### Framework versions - PEFT 0.15.2 - Transformers 4.52.3 - Pytorch 2.6.0+cu124 - Datasets 3.6.0 - Tokenizers 0.21.1