---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- whisper-event
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: WhisperTinyFinnishV3
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_11_0
      type: common_voice_11_0
      config: fi
      split: test
      args: fi
    metrics:
    - name: Wer
      type: wer
      value: 45.13758009800226
---

<!-- 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. -->

# WhisperTinyFinnishV3

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5363
- Wer: 45.1376

## 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: 3e-06
- train_batch_size: 32
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.9236        | 0.1   | 1000  | 0.7783          | 58.5187 |
| 0.727         | 0.2   | 2000  | 0.6638          | 53.1097 |
| 0.6867        | 0.3   | 3000  | 0.6113          | 50.2639 |
| 0.8348        | 0.4   | 4000  | 0.5882          | 48.2661 |
| 0.5165        | 0.5   | 5000  | 0.5679          | 47.1259 |
| 0.5509        | 0.6   | 6000  | 0.5540          | 46.6359 |
| 0.639         | 0.7   | 7000  | 0.5466          | 46.5228 |
| 0.4715        | 0.8   | 8000  | 0.5400          | 45.9763 |
| 0.6306        | 0.9   | 9000  | 0.5363          | 45.1376 |
| 0.4598        | 1.0   | 10000 | 0.5352          | 45.4768 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
