| language: | |
| - en | |
| license: apache-2.0 | |
| tags: | |
| - en-asr-leaderboard | |
| - generated_from_trainer | |
| datasets: | |
| - mn367/radio-test-dataset | |
| model-index: | |
| - name: Whisper Medium 2hr | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # Whisper Medium 2hr | |
| This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Radio dataset dataset. | |
| It achieves the following results on the evaluation set: | |
| - eval_loss: 0.4054 | |
| - eval_wer: 15.0273 | |
| - eval_runtime: 415.198 | |
| - eval_samples_per_second: 2.317 | |
| - eval_steps_per_second: 0.291 | |
| - epoch: 13.11 | |
| - step: 800 | |
| ## 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-06 | |
| - 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: 500 | |
| - training_steps: 1600 | |
| - mixed_precision_training: Native AMP | |
| ### Framework versions | |
| - Transformers 4.26.0.dev0 | |
| - Pytorch 1.13.0+cu116 | |
| - Datasets 2.8.0 | |
| - Tokenizers 0.13.2 | |