---
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: 0.3485
- Wer: 12.5880

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.5418        | 0.49  | 30   | 0.3376          | 12.7246 |
| 0.2735        | 0.98  | 60   | 0.3104          | 14.0380 |
| 0.1441        | 1.48  | 90   | 0.3110          | 14.0380 |
| 0.1241        | 1.97  | 120  | 0.3036          | 12.1572 |
| 0.0581        | 2.46  | 150  | 0.3239          | 11.6528 |
| 0.0536        | 2.95  | 180  | 0.3266          | 13.2500 |
| 0.0274        | 3.44  | 210  | 0.3464          | 12.2307 |
| 0.0224        | 3.93  | 240  | 0.3380          | 12.5775 |
| 0.0119        | 4.43  | 270  | 0.3473          | 12.7036 |
| 0.0087        | 4.92  | 300  | 0.3485          | 12.5880 |


### Framework versions

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