---
language:
- fi
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Large v3 Fine-Tuned Finnish - CommonVoice13
  results: []
---

<!-- 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 - CommonVoice13

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3318
- Wer: 25.9893

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 1.3591        | 0.42  | 50   | 0.3653          | 32.0541 |
| 0.4623        | 0.84  | 100  | 0.4383          | 35.4316 |
| 0.3229        | 1.26  | 150  | 0.4386          | 35.3672 |
| 0.2538        | 1.68  | 200  | 0.4324          | 34.4929 |
| 0.1972        | 2.11  | 250  | 0.4287          | 34.4561 |
| 0.1194        | 2.53  | 300  | 0.4235          | 33.6094 |
| 0.1132        | 2.95  | 350  | 0.3826          | 30.1767 |
| 0.0669        | 3.37  | 400  | 0.4073          | 33.0941 |
| 0.0614        | 3.79  | 450  | 0.3869          | 29.5233 |
| 0.0435        | 4.21  | 500  | 0.3942          | 30.1859 |
| 0.032         | 4.63  | 550  | 0.3839          | 27.9404 |
| 0.0184        | 5.05  | 600  | 0.3571          | 25.7500 |
| 0.0094        | 5.47  | 650  | 0.3477          | 25.8605 |
| 0.0055        | 5.89  | 700  | 0.3371          | 26.6243 |
| 0.0026        | 6.32  | 750  | 0.3329          | 25.4463 |
| 0.0015        | 6.74  | 800  | 0.3318          | 25.9893 |


### Framework versions

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