---
language:
- fi
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Large v3 Fine-Tuned Finnish
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 13.0
      type: mozilla-foundation/common_voice_13_0
      config: fi
      split: test
    metrics:
    - name: Wer
      type: wer
      value: 23.016749493833977
---

<!-- 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 v3 Fine-Tuned Finnish

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the Common Voice 13.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3344
- Wer: 23.0167

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 800
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.5817        | 0.42  | 50   | 0.4090          | 37.5023 |
| 0.4669        | 0.84  | 100  | 0.4374          | 35.8274 |
| 0.3154        | 1.26  | 150  | 0.4848          | 39.0484 |
| 0.2192        | 1.68  | 200  | 0.4313          | 34.6954 |
| 0.1985        | 2.1   | 250  | 0.4346          | 34.5205 |
| 0.1125        | 2.52  | 300  | 0.4307          | 32.8640 |
| 0.1039        | 2.94  | 350  | 0.4278          | 31.3271 |
| 0.067         | 3.36  | 400  | 0.4043          | 33.5542 |
| 0.0577        | 3.78  | 450  | 0.3911          | 40.7050 |
| 0.0461        | 4.2   | 500  | 0.3966          | 30.4712 |
| 0.0264        | 4.62  | 550  | 0.3630          | 27.2041 |
| 0.0204        | 5.04  | 600  | 0.3632          | 26.0353 |
| 0.0092        | 5.46  | 650  | 0.3448          | 24.4156 |
| 0.006         | 5.88  | 700  | 0.3284          | 23.9278 |
| 0.002         | 6.3   | 750  | 0.3334          | 23.2836 |
| 0.0019        | 6.72  | 800  | 0.3344          | 23.0167 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.15.0