--- license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - yt metrics: - wer model-index: - name: yt-special-batch8 results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: yt id type: yt args: id metrics: - name: Wer type: wer value: 100.0 --- # yt-special-batch8 This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the yt id dataset. It achieves the following results on the evaluation set: - Loss: nan - Wer: 100.0 ## 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: 8 - eval_batch_size: 4 - 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 | |:-------------:|:-----:|:----:|:---------------:|:-----:| | 0.0 | 0.17 | 1000 | nan | 100.0 | | 0.0 | 0.34 | 2000 | nan | 100.0 | | 0.0 | 0.52 | 3000 | nan | 100.0 | | 0.0 | 0.69 | 4000 | nan | 100.0 | | 0.0 | 0.86 | 5000 | nan | 100.0 | ### Framework versions - Transformers 4.31.0.dev0 - Pytorch 2.0.1+cu117 - Datasets 2.13.1 - Tokenizers 0.13.3