---
language:
- fi
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Finnish all
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 fi
      type: mozilla-foundation/common_voice_11_0
      config: fi
      split: test
      args: fi
    metrics:
    - name: Wer
      type: wer
      value: 25.43330821401658
---

<!-- 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 Finnish all

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 fi dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5334
- Wer: 25.4333

## Model description

The Model is fine-tuned for 5000 steps/updates on CV11 Finnish train+valiation data.

- Zero-shot           -   30.5 (CV9 test data, even on CV11 the WER is closer a bit higher than this)
- Fine-tuned          -   25.43 (CV11 test data)


## 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: 64
- eval_batch_size: 32
- 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0025        | 19.0  | 1000 | 0.4265          | 24.8493 |
| 0.0005        | 38.0  | 2000 | 0.4785          | 25.3203 |
| 0.0003        | 57.01 | 3000 | 0.5073          | 25.3956 |
| 0.0002        | 76.01 | 4000 | 0.5253          | 25.4333 |
| 0.0002        | 96.0  | 5000 | 0.5334          | 25.4333 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2