
<!-- 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-small-yue-mdcc-1

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2556
- Cer: 13.0495

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.5014        | 1.05  | 100  | 0.3315          | 27.2477 |
| 0.1895        | 2.11  | 200  | 0.2321          | 16.3903 |
| 0.1272        | 3.16  | 300  | 0.2210          | 15.7561 |
| 0.0759        | 4.21  | 400  | 0.2191          | 14.2006 |
| 0.0363        | 5.26  | 500  | 0.2249          | 16.1079 |
| 0.02          | 6.32  | 600  | 0.2320          | 13.4516 |
| 0.0112        | 7.37  | 700  | 0.2398          | 13.0711 |
| 0.0062        | 8.42  | 800  | 0.2497          | 13.0902 |
| 0.0048        | 9.47  | 900  | 0.2556          | 13.0495 |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "openai/whisper-small", "model-index": [{"name": "whisper-small-yue-mdcc-1", "results": []}]}
transformers tensorboard safetensors whisper automatic-speech-recognition endpoints_compatible region:us