transformers safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer fi dataset:mozilla-foundation/common_voice_13_0 base_model:openai/whisper-large-v3 license:apache-2.0 model-index endpoints_compatible region:us
---
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: 19.482790355236517
---

<!-- 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: 0.2128
- Wer: 19.4828

## 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-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.6193        | 0.21  | 50   | 0.2905          | 29.1920 |
| 0.3515        | 0.42  | 100  | 0.3581          | 32.2014 |
| 0.3433        | 0.63  | 150  | 0.3497          | 43.9812 |
| 0.3196        | 0.84  | 200  | 0.3080          | 27.9956 |
| 0.2597        | 1.05  | 250  | 0.3213          | 27.5630 |
| 0.1368        | 1.26  | 300  | 0.3088          | 29.0263 |
| 0.1316        | 1.47  | 350  | 0.3018          | 27.0569 |
| 0.1193        | 1.68  | 400  | 0.2948          | 28.5846 |
| 0.1219        | 1.89  | 450  | 0.2608          | 25.1979 |
| 0.0738        | 2.11  | 500  | 0.2645          | 30.9682 |
| 0.042         | 2.32  | 550  | 0.2493          | 23.2008 |
| 0.0406        | 2.53  | 600  | 0.2589          | 21.6823 |
| 0.0317        | 2.74  | 650  | 0.2391          | 24.9862 |
| 0.0336        | 2.95  | 700  | 0.2217          | 21.6639 |
| 0.0127        | 3.16  | 750  | 0.2126          | 20.3939 |
| 0.0085        | 3.37  | 800  | 0.2128          | 19.4828 |


### Framework versions

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