---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: whisper-tiny-fi
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_11_0
      type: common_voice_11_0
      config: fi
      split: None
      args: fi
    metrics:
    - name: Wer
      type: wer
      value: 309.7839418813096
---

<!-- 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-tiny-fi

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: 0.7638
- Wer: 309.7839

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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      |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.986         | 0.3690  | 100  | 1.5979          | 83.1116  |
| 0.755         | 0.7380  | 200  | 0.7632          | 82.2813  |
| 0.57          | 1.1070  | 300  | 0.7001          | 75.4128  |
| 0.517         | 1.4760  | 400  | 0.6558          | 76.1110  |
| 0.4948        | 1.8450  | 500  | 0.6328          | 71.7426  |
| 0.3598        | 2.2140  | 600  | 0.6191          | 69.7519  |
| 0.3708        | 2.5830  | 700  | 0.6093          | 71.5067  |
| 0.3379        | 2.9520  | 800  | 0.5944          | 70.6010  |
| 0.2184        | 3.3210  | 900  | 0.5993          | 69.8085  |
| 0.2335        | 3.6900  | 1000 | 0.5836          | 69.1197  |
| 0.1763        | 4.0590  | 1100 | 0.5925          | 69.6292  |
| 0.1648        | 4.4280  | 1200 | 0.5940          | 72.7805  |
| 0.1471        | 4.7970  | 1300 | 0.5947          | 74.0542  |
| 0.0922        | 5.1661  | 1400 | 0.6138          | 72.4974  |
| 0.0989        | 5.5351  | 1500 | 0.6071          | 73.5541  |
| 0.095         | 5.9041  | 1600 | 0.6121          | 75.1392  |
| 0.0554        | 6.2731  | 1700 | 0.6237          | 76.0732  |
| 0.0606        | 6.6421  | 1800 | 0.6240          | 79.8000  |
| 0.0544        | 7.0111  | 1900 | 0.6418          | 83.9419  |
| 0.0372        | 7.3801  | 2000 | 0.6391          | 91.3105  |
| 0.0414        | 7.7491  | 2100 | 0.6471          | 81.3850  |
| 0.0223        | 8.1181  | 2200 | 0.6521          | 104.4249 |
| 0.0256        | 8.4871  | 2300 | 0.6587          | 104.8684 |
| 0.0233        | 8.8561  | 2400 | 0.6669          | 119.1056 |
| 0.0159        | 9.2251  | 2500 | 0.6907          | 107.2271 |
| 0.0162        | 9.5941  | 2600 | 0.6879          | 140.2585 |
| 0.0156        | 9.9631  | 2700 | 0.6933          | 185.6024 |
| 0.01          | 10.3321 | 2800 | 0.6958          | 259.4584 |
| 0.0099        | 10.7011 | 2900 | 0.7037          | 205.2363 |
| 0.0074        | 11.0701 | 3000 | 0.7080          | 246.1836 |
| 0.0074        | 11.4391 | 3100 | 0.7141          | 240.3906 |
| 0.0074        | 11.8081 | 3200 | 0.7159          | 196.5185 |
| 0.0053        | 12.1771 | 3300 | 0.7246          | 216.1242 |
| 0.0057        | 12.5461 | 3400 | 0.7310          | 215.3033 |
| 0.0056        | 12.9151 | 3500 | 0.7343          | 232.3521 |
| 0.0044        | 13.2841 | 3600 | 0.7374          | 234.0976 |
| 0.0047        | 13.6531 | 3700 | 0.7420          | 248.5989 |
| 0.0046        | 14.0221 | 3800 | 0.7482          | 245.2684 |
| 0.0041        | 14.3911 | 3900 | 0.7480          | 270.2236 |
| 0.0038        | 14.7601 | 4000 | 0.7481          | 294.0466 |
| 0.0037        | 15.1292 | 4100 | 0.7547          | 263.7513 |
| 0.0037        | 15.4982 | 4200 | 0.7551          | 280.0359 |
| 0.0035        | 15.8672 | 4300 | 0.7568          | 270.1198 |
| 0.0032        | 16.2362 | 4400 | 0.7574          | 286.9327 |
| 0.0032        | 16.6052 | 4500 | 0.7611          | 286.9516 |
| 0.0035        | 16.9742 | 4600 | 0.7618          | 309.7368 |
| 0.0032        | 17.3432 | 4700 | 0.7632          | 298.6508 |
| 0.0031        | 17.7122 | 4800 | 0.7632          | 304.3778 |
| 0.0029        | 18.0812 | 4900 | 0.7637          | 304.8306 |
| 0.003         | 18.4502 | 5000 | 0.7638          | 309.7839 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1