--- language: - multilingual license: apache-2.0 base_model: openai/whisper-medium tags: - hf-asr-leaderboard - generated_from_trainer datasets: - mozilla-foundation/common_voice_11_0 metrics: - wer model-index: - name: TMP prvontni trenovani jazyk en, train en de en similar results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: xbilek25/train_set_1st_1000_de_en_de type: mozilla-foundation/common_voice_11_0 args: 'config: ende, split: train' metrics: - name: Wer type: wer value: 17.387261738726174 --- # TMP prvontni trenovani jazyk en, train en de en similar This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the xbilek25/train_set_1st_1000_de_en_de dataset. It achieves the following results on the evaluation set: - Loss: 0.3401 - Wer: 17.3873 ## 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: 16 - 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: 1 - training_steps: 2000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.0979 | 1.12 | 500 | 0.2481 | 19.0875 | | 0.0097 | 3.12 | 1000 | 0.2917 | 16.7763 | | 0.0017 | 5.12 | 1500 | 0.3298 | 16.9689 | | 0.0011 | 7.12 | 2000 | 0.3401 | 17.3873 | ### Framework versions - Transformers 4.37.2 - Pytorch 2.2.1+cu121 - Datasets 2.19.0 - Tokenizers 0.15.2