--- language: - fi license: apache-2.0 base_model: openai/whisper-large-v3 tags: - hf-asr-leaderboard - generated_from_trainer metrics: - wer model-index: - name: Whisper Large v3 Fine-Tuned Finnish - CommonVoice13 results: [] --- # Whisper Large v3 Fine-Tuned Finnish - CommonVoice13 This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.3858 - Wer: 21.6363 It achieves the following results on the Test set: - Eval_Wer: 21.636296705319342 - Eval_NormalizedWer: 18.727590328215502 ## 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: 5e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 8 - total_train_batch_size: 64 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 50 - training_steps: 800 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.0049 | 0.84 | 50 | 0.4045 | 27.8851 | | 0.0264 | 1.68 | 100 | 0.4482 | 29.3852 | | 0.0189 | 2.53 | 150 | 0.4076 | 26.6980 | | 0.0129 | 3.37 | 200 | 0.3772 | 24.5905 | | 0.0087 | 4.21 | 250 | 0.3875 | 25.5108 | | 0.0054 | 5.05 | 300 | 0.3754 | 24.9034 | | 0.0035 | 5.89 | 350 | 0.3742 | 23.5505 | | 0.0014 | 6.74 | 400 | 0.3823 | 23.4677 | | 0.0014 | 7.58 | 450 | 0.3914 | 23.5781 | | 0.0012 | 8.42 | 500 | 0.3771 | 22.3173 | | 0.0007 | 9.26 | 550 | 0.3812 | 21.8756 | | 0.0002 | 10.11 | 600 | 0.3812 | 21.7191 | | 0.0002 | 10.95 | 650 | 0.3825 | 21.6547 | | 0.0001 | 11.79 | 700 | 0.3844 | 21.6363 | | 0.0001 | 12.63 | 750 | 0.3854 | 21.5995 | | 0.0001 | 13.47 | 800 | 0.3858 | 21.6363 | ### Framework versions - Transformers 4.37.0.dev0 - Pytorch 2.0.1 - Datasets 2.16.1 - Tokenizers 0.15.0