---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: whisper-training-blog
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: fleurs
      type: fleurs
      config: sv_se
      split: validation
      args: sv_se
    metrics:
    - name: Wer
      type: wer
      value: 180.05748044068338
---

<!-- 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-training-blog

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0050
- Wer: 180.0575

## 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: 7.5e-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_ratio: 0.3
- training_steps: 448
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4112        | 0.1   | 44   | 1.4919          | 245.3457 |
| 1.0502        | 0.2   | 88   | 1.2255          | 220.1501 |
| 0.9033        | 0.29  | 132  | 1.1203          | 206.2430 |
| 0.8141        | 1.06  | 176  | 1.0675          | 201.9639 |
| 0.8029        | 1.16  | 220  | 1.0394          | 178.3650 |
| 0.6324        | 1.25  | 264  | 1.0301          | 221.2997 |
| 0.6972        | 2.02  | 308  | 1.0134          | 176.6725 |
| 0.6052        | 2.12  | 352  | 1.0065          | 194.7150 |
| 0.6047        | 2.21  | 396  | 1.0030          | 160.9133 |
| 0.5849        | 2.31  | 440  | 1.0050          | 180.0575 |


### Framework versions

- Transformers 4.27.3
- Pytorch 2.0.0+cu118
- Datasets 2.10.1
- Tokenizers 0.13.3