---
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: 0.2418
- Wer: 16.0707

## 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-06
- 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: 7000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.2962        | 0.0727 | 1000 | 0.3163          | 20.0659 |
| 0.2756        | 0.1454 | 2000 | 0.2962          | 19.2670 |
| 0.2405        | 0.2181 | 3000 | 0.2771          | 18.1353 |
| 0.2917        | 0.2908 | 4000 | 0.2644          | 17.5769 |
| 0.2117        | 0.3635 | 5000 | 0.2536          | 16.7275 |
| 0.2334        | 0.4362 | 6000 | 0.2455          | 16.3825 |
| 0.2408        | 0.5089 | 7000 | 0.2418          | 16.0707 |


### Framework versions

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