---
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: 0.1506
- Wer: 5.1288

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.4241        | 0.38  | 30   | 0.1816          | 7.9883 |
| 0.1734        | 0.75  | 60   | 0.1585          | 6.3247 |
| 0.1334        | 1.12  | 90   | 0.1560          | 5.9874 |
| 0.0787        | 1.5   | 120  | 0.1468          | 6.0718 |
| 0.0745        | 1.88  | 150  | 0.1465          | 7.3674 |
| 0.0512        | 2.25  | 180  | 0.1452          | 7.1297 |
| 0.0314        | 2.62  | 210  | 0.1405          | 5.4814 |
| 0.0321        | 3.0   | 240  | 0.1376          | 5.4125 |
| 0.0154        | 3.38  | 270  | 0.1469          | 5.2208 |
| 0.0144        | 3.75  | 300  | 0.1493          | 5.2515 |
| 0.011         | 4.12  | 330  | 0.1443          | 5.0905 |
| 0.0064        | 4.5   | 360  | 0.1502          | 5.1058 |
| 0.007         | 4.88  | 390  | 0.1506          | 5.1288 |


### Framework versions

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