---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-v2-3swissdatasets
  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-v2-3swissdatasets

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: 0.2758
- Wer: 17.7832

## 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: 5e-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: 500
- training_steps: 6000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.5575        | 0.0727 | 1000 | 0.6201          | 35.9145 |
| 0.4618        | 0.1454 | 2000 | 0.5084          | 30.6525 |
| 0.3571        | 0.2181 | 3000 | 0.4122          | 25.1587 |
| 0.3845        | 0.2908 | 4000 | 0.3702          | 23.1700 |
| 0.2471        | 0.3635 | 5000 | 0.3127          | 19.8575 |
| 0.2415        | 0.4362 | 6000 | 0.2758          | 17.7832 |


### Framework versions

- Transformers 4.44.1
- Pytorch 2.3.1+cu118
- Datasets 3.2.0
- Tokenizers 0.19.1