--- language: - fr license: apache-2.0 tags: - whisper-event - generated_from_trainer datasets: - mozilla-foundation/common_voice_11_0 metrics: - wer model-index: - name: Whisper Tiny French Cased results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: mozilla-foundation/common_voice_11_0 fr type: mozilla-foundation/common_voice_11_0 config: fr split: test args: fr metrics: - name: Wer type: wer value: 33.06549172161867 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: google/fleurs fr_fr type: google/fleurs config: fr_fr split: test args: fr_fr metrics: - name: Wer type: wer value: 36.69 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: facebook/voxpopuli fr type: facebook/voxpopuli config: fr split: test args: fr metrics: - name: Wer type: wer value: 32.71 --- # Whisper Tiny French Cased This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the mozilla-foundation/common_voice_11_0 fr dataset. It achieves the following results on the evaluation set: - Loss: 0.6509 - Wer on `mozilla-foundation/common_voice_11_0` `fr`: 33.0655 - Wer on `google/fleurs` `fr_fr`: 36.69 - Wer on `facebook/voxpopuli` `fr`: 32.71 ## 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: 5000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.7185 | 0.2 | 1000 | 0.7608 | 38.1636 | | 0.6052 | 1.2 | 2000 | 0.6949 | 34.9513 | | 0.4467 | 2.2 | 3000 | 0.6708 | 34.3393 | | 0.4773 | 3.2 | 4000 | 0.6536 | 33.2102 | | 0.4479 | 4.2 | 5000 | 0.6509 | 33.0655 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.11.0+cu102 - Datasets 2.7.1.dev0 - Tokenizers 0.13.2