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# Whisper Large V2

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3074
- Wer: 8.5830

## 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: 3e-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: 20
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.5501        | 0.49  | 30   | 0.2986          | 11.6004 |
| 0.2904        | 0.98  | 60   | 0.2648          | 10.1717 |
| 0.1426        | 1.48  | 90   | 0.2685          | 10.5448 |
| 0.1339        | 1.97  | 120  | 0.2609          | 8.9349  |
| 0.0571        | 2.46  | 150  | 0.2817          | 8.9135  |
| 0.0585        | 2.95  | 180  | 0.2846          | 8.5830  |
| 0.0291        | 3.44  | 210  | 0.3041          | 10.2783 |
| 0.0201        | 3.93  | 240  | 0.2999          | 8.6470  |
| 0.0115        | 4.43  | 270  | 0.3039          | 8.4551  |
| 0.0084        | 4.92  | 300  | 0.3074          | 8.5830  |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0

{"language": ["nl"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "base_model": "openai/whisper-large-v2", "model-index": [{"name": "Whisper Large V2", "results": []}]}
transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer nl base_model:openai/whisper-large-v2 license:apache-2.0 endpoints_compatible region:us