language: | |
- en | |
license: apache-2.0 | |
tags: | |
- en-asr-leaderboard | |
- generated_from_trainer | |
datasets: | |
- mn367/radio-test-dataset | |
model-index: | |
- name: Whisper Medium 1hr | |
results: [] | |
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should probably proofread and complete it, then remove this comment. --> | |
# Whisper Medium 1hr | |
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: 0.6053 | |
- eval_wer: 17.5426 | |
- eval_runtime: 651.6941 | |
- eval_samples_per_second: 2.363 | |
- eval_steps_per_second: 0.296 | |
- epoch: 37.5 | |
- step: 900 | |
## 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 | |