---
language:
- nl
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Large V2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# 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: 0.3047
- Wer: 8.8078

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.5556        | 0.49  | 30   | 0.3116          | 14.7321 |
| 0.2736        | 0.98  | 60   | 0.2567          | 12.1736 |
| 0.1361        | 1.48  | 90   | 0.2769          | 10.2024 |
| 0.1364        | 1.97  | 120  | 0.2525          | 9.1643  |
| 0.0582        | 2.46  | 150  | 0.2734          | 10.9049 |
| 0.0568        | 2.95  | 180  | 0.2669          | 9.2796  |
| 0.0289        | 3.44  | 210  | 0.2841          | 8.7973  |
| 0.0206        | 3.93  | 240  | 0.2877          | 8.7868  |
| 0.0107        | 4.43  | 270  | 0.3009          | 8.8393  |
| 0.0089        | 4.92  | 300  | 0.3047          | 8.8078  |


### Framework versions

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