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# whisper-smal-sq-30000

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3562
- Wer: 0.2949

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 80
- training_steps: 2000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.5187        | 0.27  | 250  | 0.5478          | 0.4670 |
| 0.4095        | 0.53  | 500  | 0.4469          | 0.3795 |
| 0.3466        | 0.8   | 750  | 0.4068          | 0.3574 |
| 0.3083        | 1.07  | 1000 | 0.3856          | 0.3218 |
| 0.288         | 1.33  | 1250 | 0.3733          | 0.3122 |
| 0.2911        | 1.6   | 1500 | 0.3628          | 0.3038 |
| 0.2697        | 1.87  | 1750 | 0.3569          | 0.2993 |
| 0.2462        | 2.13  | 2000 | 0.3562          | 0.2949 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.3.0.dev20231220
- Datasets 2.14.5
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "base_model": "openai/whisper-small", "model-index": [{"name": "whisper-smal-sq-30000", "results": []}]}
transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer base_model:openai/whisper-small license:apache-2.0 endpoints_compatible region:us