---
library_name: transformers
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: 0.2953
- Wer: 11.3276

## 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: 12
- 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     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.5452        | 0.4839 | 15   | 0.3714          | 23.2724 |
| 0.2911        | 0.9677 | 30   | 0.2866          | 18.6494 |
| 0.1304        | 1.4516 | 45   | 0.2713          | 13.6270 |
| 0.1196        | 1.9355 | 60   | 0.2595          | 12.7436 |
| 0.0595        | 2.4194 | 75   | 0.2615          | 11.8964 |
| 0.043         | 2.9032 | 90   | 0.2700          | 13.0098 |
| 0.0229        | 3.3871 | 105  | 0.2854          | 15.4786 |
| 0.0176        | 3.8710 | 120  | 0.2747          | 12.9856 |
| 0.0101        | 4.3548 | 135  | 0.2882          | 11.1340 |
| 0.0069        | 4.8387 | 150  | 0.2953          | 11.3276 |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1