---
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper small Luxembourgish
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: google/fleurs lb_lu
      type: google/fleurs
      config: lb_lu
      split: test
    metrics:
    - name: Wer
      type: wer
      value: 39.49904580152672
---

<!-- 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 small Luxembourgish

This model is a fine-tuned version of [bofenghuang/whisper-small-cv11-german-punct](https://huggingface.co/bofenghuang/whisper-small-cv11-german-punct) on the google/fleurs lb_lu dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1857
- Wer: 39.4990

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.0618        | 38.46  | 500  | 1.0104          | 43.2968 |
| 0.0055        | 76.92  | 1000 | 1.0684          | 40.1288 |
| 0.0024        | 115.38 | 1500 | 1.1056          | 40.9447 |
| 0.0014        | 153.85 | 2000 | 1.1280          | 39.7615 |
| 0.0013        | 192.31 | 2500 | 1.1415          | 39.9857 |
| 0.0008        | 230.77 | 3000 | 1.1573          | 39.7996 |
| 0.0006        | 269.23 | 3500 | 1.1682          | 40.0095 |
| 0.0006        | 307.69 | 4000 | 1.1769          | 39.7233 |
| 0.0005        | 346.15 | 4500 | 1.1826          | 39.5134 |
| 0.0004        | 384.62 | 5000 | 1.1857          | 39.4990 |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2