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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: 0.4621
- Wer: 17.7714

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.7903        | 0.55  | 30   | 0.4799          | 21.8700 |
| 0.3838        | 1.09  | 60   | 0.4107          | 18.9081 |
| 0.2236        | 1.64  | 90   | 0.4067          | 28.0179 |
| 0.1796        | 2.18  | 120  | 0.4097          | 21.1335 |
| 0.1006        | 2.73  | 150  | 0.4123          | 17.6593 |
| 0.0671        | 3.27  | 180  | 0.4287          | 18.7960 |
| 0.04          | 3.82  | 210  | 0.4426          | 18.5239 |
| 0.0242        | 4.36  | 240  | 0.4586          | 18.0275 |
| 0.017         | 4.91  | 270  | 0.4621          | 17.7714 |


### 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