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# whisper-small-yue-fold-3

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: 0.2815
- Wer: 83.6735

## 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: 32
- eval_batch_size: 16
- 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: 400
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.7804        | 0.38  | 50   | 2.2963          | 123.7477 |
| 0.7908        | 0.75  | 100  | 0.4247          | 199.6289 |
| 0.305         | 1.13  | 150  | 0.3275          | 124.2115 |
| 0.2708        | 1.5   | 200  | 0.2999          | 104.6382 |
| 0.2586        | 1.88  | 250  | 0.2925          | 74.5826  |
| 0.1571        | 2.26  | 300  | 0.2853          | 78.6642  |
| 0.1575        | 2.63  | 350  | 0.2780          | 75.0464  |
| 0.1431        | 3.01  | 400  | 0.2815          | 83.6735  |


### 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-fold-3", "results": []}]}
transformers safetensors whisper automatic-speech-recognition generated_from_trainer base_model:openai/whisper-small license:apache-2.0 endpoints_compatible region:us