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# whisper_tiny-mini2

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1008
- Wer: 5.5449

## 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: 100
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 2.0118        | 1.49  | 100  | 1.8148          | 15.4876 |
| 0.3222        | 2.99  | 200  | 0.3016          | 8.0306  |
| 0.0315        | 4.48  | 300  | 0.1206          | 4.7801  |
| 0.0098        | 5.97  | 400  | 0.1097          | 4.7801  |
| 0.0025        | 7.46  | 500  | 0.1024          | 5.3537  |
| 0.0017        | 8.96  | 600  | 0.1044          | 5.1625  |
| 0.0011        | 10.45 | 700  | 0.1033          | 4.7801  |
| 0.001         | 11.94 | 800  | 0.1013          | 5.5449  |
| 0.0008        | 13.43 | 900  | 0.1009          | 5.3537  |
| 0.0008        | 14.93 | 1000 | 0.1008          | 5.5449  |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"language": ["en"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "base_model": "openai/whisper-tiny", "model-index": [{"name": "whisper_tiny-mini2", "results": []}]}
transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer en base_model:openai/whisper-tiny license:apache-2.0 endpoints_compatible region:us