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# whisper-small-yue

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: 0.3647
- Wer: 73.2309

## 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: 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: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.9266        | 0.15  | 50   | 2.6136          | 142.9438 |
| 1.0635        | 0.3   | 100  | 0.5730          | 216.4982 |
| 0.373         | 0.45  | 150  | 0.3679          | 319.4501 |
| 0.3004        | 0.6   | 200  | 0.3362          | 170.2386 |
| 0.3078        | 0.76  | 250  | 0.3206          | 118.7626 |
| 0.2687        | 0.91  | 300  | 0.3075          | 93.4897  |
| 0.204         | 1.06  | 350  | 0.3017          | 74.0801  |
| 0.1954        | 1.21  | 400  | 0.3015          | 77.5981  |
| 0.1857        | 1.36  | 450  | 0.2981          | 76.9106  |
| 0.1833        | 1.51  | 500  | 0.3029          | 75.3336  |
| 0.198         | 1.66  | 550  | 0.2972          | 76.8702  |
| 0.1902        | 1.81  | 600  | 0.2883          | 68.8233  |
| 0.196         | 1.96  | 650  | 0.2854          | 68.7829  |
| 0.0732        | 2.11  | 700  | 0.2895          | 69.9151  |
| 0.07          | 2.27  | 750  | 0.2939          | 72.2604  |
| 0.0853        | 2.42  | 800  | 0.3137          | 74.4440  |
| 0.0788        | 2.57  | 850  | 0.3133          | 71.3304  |
| 0.0713        | 2.72  | 900  | 0.2974          | 70.6025  |
| 0.0773        | 2.87  | 950  | 0.2884          | 75.2527  |
| 0.072         | 3.02  | 1000 | 0.2923          | 69.8342  |
| 0.0418        | 3.17  | 1050 | 0.2948          | 73.5544  |
| 0.0318        | 3.32  | 1100 | 0.2965          | 74.2822  |
| 0.0298        | 3.47  | 1150 | 0.3002          | 69.4703  |
| 0.036         | 3.63  | 1200 | 0.3004          | 70.1577  |
| 0.0307        | 3.78  | 1250 | 0.3015          | 74.3631  |
| 0.0403        | 3.93  | 1300 | 0.3000          | 71.4517  |
| 0.0152        | 4.08  | 1350 | 0.3117          | 68.7829  |
| 0.0168        | 4.23  | 1400 | 0.3140          | 71.3708  |
| 0.0136        | 4.38  | 1450 | 0.3225          | 68.1359  |
| 0.0145        | 4.53  | 1500 | 0.3244          | 70.6025  |
| 0.0188        | 4.68  | 1550 | 0.3217          | 72.0178  |
| 0.0202        | 4.83  | 1600 | 0.3087          | 70.8047  |
| 0.0184        | 4.98  | 1650 | 0.3225          | 72.6648  |
| 0.0082        | 5.14  | 1700 | 0.3285          | 70.2386  |
| 0.0066        | 5.29  | 1750 | 0.3288          | 71.0473  |
| 0.0091        | 5.44  | 1800 | 0.3370          | 68.2572  |
| 0.0063        | 5.59  | 1850 | 0.3299          | 71.5730  |
| 0.0093        | 5.74  | 1900 | 0.3311          | 69.3490  |
| 0.0079        | 5.89  | 1950 | 0.3456          | 75.4953  |
| 0.0087        | 6.04  | 2000 | 0.3357          | 77.5576  |
| 0.0052        | 6.19  | 2050 | 0.3364          | 79.6199  |
| 0.005         | 6.34  | 2100 | 0.3376          | 75.1314  |
| 0.0032        | 6.5   | 2150 | 0.3336          | 75.3740  |
| 0.004         | 6.65  | 2200 | 0.3441          | 74.7271  |
| 0.003         | 6.8   | 2250 | 0.3446          | 72.8265  |
| 0.0029        | 6.95  | 2300 | 0.3483          | 70.5216  |
| 0.002         | 7.1   | 2350 | 0.3532          | 74.2822  |
| 0.0014        | 7.25  | 2400 | 0.3469          | 73.5948  |
| 0.0015        | 7.4   | 2450 | 0.3494          | 75.9806  |
| 0.001         | 7.55  | 2500 | 0.3549          | 75.1314  |
| 0.0053        | 7.7   | 2550 | 0.3545          | 73.2309  |
| 0.0025        | 7.85  | 2600 | 0.3563          | 72.7457  |
| 0.001         | 8.01  | 2650 | 0.3562          | 73.5140  |
| 0.001         | 8.16  | 2700 | 0.3594          | 75.1719  |
| 0.0012        | 8.31  | 2750 | 0.3610          | 72.7052  |
| 0.0007        | 8.46  | 2800 | 0.3611          | 72.9478  |
| 0.0016        | 8.61  | 2850 | 0.3629          | 72.8265  |
| 0.0007        | 8.76  | 2900 | 0.3633          | 73.7161  |
| 0.0015        | 8.91  | 2950 | 0.3647          | 73.2309  |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 1.12.1
- Datasets 2.15.0
- Tokenizers 0.15.0

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