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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: 0.4367
- Wer: 13.2014

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.7481        | 0.55  | 30   | 0.4470          | 24.0337 |
| 0.3791        | 1.09  | 60   | 0.3935          | 17.3940 |
| 0.2077        | 1.64  | 90   | 0.3841          | 14.4015 |
| 0.1739        | 2.18  | 120  | 0.3804          | 14.5729 |
| 0.0918        | 2.73  | 150  | 0.4027          | 15.1808 |
| 0.0684        | 3.27  | 180  | 0.4156          | 15.3367 |
| 0.0391        | 3.82  | 210  | 0.4038          | 15.5393 |
| 0.0197        | 4.36  | 240  | 0.4326          | 13.5287 |
| 0.0128        | 4.91  | 270  | 0.4367          | 13.2014 |


### 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