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# whisper_medium_zh

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9767
- Wer: 96.0
- Cer: 12.6058

## 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: 4
- 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: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer  | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:----:|:-------:|
| No log        | 0.48  | 10   | 2.7665          | 98.0 | 13.0762 |
| No log        | 0.95  | 20   | 2.6914          | 98.0 | 13.0762 |
| 2.4583        | 1.43  | 30   | 2.2921          | 98.0 | 12.8881 |
| 2.4583        | 1.9   | 40   | 1.9767          | 96.0 | 12.6058 |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "whisper_medium_zh", "results": []}]}
transformers pytorch tensorboard whisper automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us