---
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: 0.4660
- Wer: 14.5440

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.7649        | 0.55  | 30   | 0.4569          | 21.4116 |
| 0.3718        | 1.09  | 60   | 0.4107          | 14.9247 |
| 0.2053        | 1.64  | 90   | 0.3970          | 17.1451 |
| 0.1836        | 2.18  | 120  | 0.4242          | 14.0523 |
| 0.092         | 2.73  | 150  | 0.4120          | 14.4330 |
| 0.0648        | 3.27  | 180  | 0.4352          | 15.5115 |
| 0.0359        | 3.82  | 210  | 0.4290          | 15.0991 |
| 0.0205        | 4.36  | 240  | 0.4587          | 14.6392 |
| 0.0132        | 4.91  | 270  | 0.4660          | 14.5440 |


### Framework versions

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