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---
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: 0.3074
- Wer: 8.5830
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.5501 | 0.49 | 30 | 0.2986 | 11.6004 |
| 0.2904 | 0.98 | 60 | 0.2648 | 10.1717 |
| 0.1426 | 1.48 | 90 | 0.2685 | 10.5448 |
| 0.1339 | 1.97 | 120 | 0.2609 | 8.9349 |
| 0.0571 | 2.46 | 150 | 0.2817 | 8.9135 |
| 0.0585 | 2.95 | 180 | 0.2846 | 8.5830 |
| 0.0291 | 3.44 | 210 | 0.3041 | 10.2783 |
| 0.0201 | 3.93 | 240 | 0.2999 | 8.6470 |
| 0.0115 | 4.43 | 270 | 0.3039 | 8.4551 |
| 0.0084 | 4.92 | 300 | 0.3074 | 8.5830 |
### Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0
|