--- language: - it license: apache-2.0 tags: - generated_from_trainer base_model: openai/whisper-medium datasets: - mozilla-foundation/common_voice_17_0 metrics: - wer model-index: - name: Whisper Medium it results: - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: Common Voice 17.0 type: mozilla-foundation/common_voice_17_0 config: it split: test args: it metrics: - type: wer value: 5.709779804285139 name: Wer - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: google/fleurs type: google/fleurs config: it_it split: test metrics: - type: wer value: 4.47 name: WER - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: facebook/multilingual_librispeech type: facebook/multilingual_librispeech config: italian split: test metrics: - type: wer value: 17.25 name: WER - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: facebook/voxpopuli type: facebook/voxpopuli config: it split: test metrics: - type: wer value: 18.75 name: WER pipeline_tag: automatic-speech-recognition --- # Whisper Medium it This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set: - Loss: 0.1462 - Wer: 5.7098 ## 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: 8 - 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 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:------:| | 0.1755 | 0.1730 | 1000 | 0.1974 | 8.0595 | | 0.157 | 0.3461 | 2000 | 0.1776 | 7.1199 | | 0.1287 | 0.5191 | 3000 | 0.1622 | 6.5201 | | 0.1287 | 0.6922 | 4000 | 0.1521 | 5.9863 | | 0.1168 | 0.8652 | 5000 | 0.1462 | 5.7098 | ### Framework versions - Transformers 4.42.0.dev0 - Pytorch 2.3.0+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1