--- language: - sv - 'no' - da license: apache-2.0 tags: - whisper-event - generated_from_trainer datasets: - mozilla-foundation/common_voice_11_0 - mozilla-foundation/common_voice_11_0 - mozilla-foundation/common_voice_11_0 - babelbox/babelbox_voice - NbAiLab/NST - NbAiLab/NPSC - google/fleurs - google/fleurs - google/fleurs metrics: - wer model-index: - name: Whisper Medium Nordic results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: mozilla-foundation/common_voice_11_0 type: mozilla-foundation/common_voice_11_0 config: sv-SE split: test metrics: - name: Wer type: wer value: 11.307923879152778 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: babelbox/babelbox_voice type: babelbox/babelbox_voice metrics: - name: Wer type: wer value: 11.307923879152778 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: NbAiLab/NST type: NbAiLab/NST metrics: - name: Wer type: wer value: 11.307923879152778 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: NbAiLab/NPSC type: NbAiLab/NPSC metrics: - name: Wer type: wer value: 11.307923879152778 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: google/fleurs type: google/fleurs metrics: - name: Wer type: wer value: 11.307923879152778 --- # Whisper Medium Nordic This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_11_0, the mozilla-foundation/common_voice_11_0, the mozilla-foundation/common_voice_11_0, the babelbox/babelbox_voice, the NbAiLab/NST, the NbAiLab/NPSC, the google/fleurs, the google/fleurs and the google/fleurs datasets. It achieves the following results on the evaluation set: - Loss: 0.2129 - Wer: 11.3079 ## 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: 3e-06 - 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_ratio: 0.1 - training_steps: 10000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:-----:|:---------------:|:-------:| | 0.3056 | 0.1 | 1000 | 0.2670 | 99.9221 | | 0.16 | 0.2 | 2000 | 0.2322 | 99.6640 | | 0.1309 | 0.3 | 3000 | 0.2152 | 98.9759 | | 0.097 | 0.4 | 4000 | 0.2112 | 100.0 | | 0.091 | 0.5 | 5000 | 0.2094 | 99.7312 | | 0.1098 | 0.6 | 6000 | 0.2098 | 98.6077 | | 0.0637 | 0.7 | 7000 | 0.2148 | 98.4625 | | 0.0718 | 0.8 | 8000 | 0.2151 | 99.8710 | | 0.0517 | 0.9 | 9000 | 0.2175 | 97.2342 | | 0.0465 | 1.0 | 10000 | 0.2129 | 96.3552 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.13.1+cu117 - Datasets 2.7.1.dev0 - Tokenizers 0.13.2