--- language: - fi license: apache-2.0 base_model: openai/whisper-large-v3 tags: - hf-asr-leaderboard - generated_from_trainer datasets: - mozilla-foundation/common_voice_13_0 metrics: - wer model-index: - name: Whisper Large v3 Fine-Tuned Finnish results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 13.0 type: mozilla-foundation/common_voice_13_0 config: fi split: test metrics: - name: Wer type: wer value: 19.482790355236517 --- # Whisper Large v3 Fine-Tuned Finnish This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the Common Voice 13.0 dataset. It achieves the following results on the evaluation set: - Loss: 0.2128 - Wer: 19.4828 ## 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: 2 - total_train_batch_size: 16 - 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 | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.6193 | 0.21 | 50 | 0.2905 | 29.1920 | | 0.3515 | 0.42 | 100 | 0.3581 | 32.2014 | | 0.3433 | 0.63 | 150 | 0.3497 | 43.9812 | | 0.3196 | 0.84 | 200 | 0.3080 | 27.9956 | | 0.2597 | 1.05 | 250 | 0.3213 | 27.5630 | | 0.1368 | 1.26 | 300 | 0.3088 | 29.0263 | | 0.1316 | 1.47 | 350 | 0.3018 | 27.0569 | | 0.1193 | 1.68 | 400 | 0.2948 | 28.5846 | | 0.1219 | 1.89 | 450 | 0.2608 | 25.1979 | | 0.0738 | 2.11 | 500 | 0.2645 | 30.9682 | | 0.042 | 2.32 | 550 | 0.2493 | 23.2008 | | 0.0406 | 2.53 | 600 | 0.2589 | 21.6823 | | 0.0317 | 2.74 | 650 | 0.2391 | 24.9862 | | 0.0336 | 2.95 | 700 | 0.2217 | 21.6639 | | 0.0127 | 3.16 | 750 | 0.2126 | 20.3939 | | 0.0085 | 3.37 | 800 | 0.2128 | 19.4828 | ### Framework versions - Transformers 4.37.0.dev0 - Pytorch 2.0.1 - Datasets 2.16.1 - Tokenizers 0.15.0