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: mozilla-foundation/common_voice_13_0
      type: mozilla-foundation/common_voice_13_0
      config: fi
      split: None
    metrics:
    - name: Wer
      type: wer
      value: 27.139701822197683
---

<!-- 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 mozilla-foundation/common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3970
- Wer: 27.1397

## 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: 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: 1600
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.7157        | 0.21  | 50   | 0.4892          | 42.8216 |
| 0.6602        | 0.42  | 100  | 0.6444          | 58.3379 |
| 0.5952        | 0.63  | 150  | 0.6134          | 52.3560 |
| 0.5649        | 0.84  | 200  | 0.5645          | 53.3499 |
| 0.5078        | 1.05  | 250  | 0.5867          | 69.4736 |
| 0.289         | 1.26  | 300  | 0.6150          | 55.5034 |
| 0.3318        | 1.47  | 350  | 0.5309          | 40.3000 |
| 0.2859        | 1.68  | 400  | 0.5462          | 41.3584 |
| 0.3091        | 1.89  | 450  | 0.4891          | 38.6159 |
| 0.2089        | 2.11  | 500  | 0.5305          | 41.0915 |
| 0.148         | 2.32  | 550  | 0.5124          | 37.8888 |
| 0.1538        | 2.53  | 600  | 0.5075          | 36.9225 |
| 0.1515        | 2.74  | 650  | 0.5187          | 37.9440 |
| 0.1532        | 2.95  | 700  | 0.4666          | 35.4040 |
| 0.0982        | 3.16  | 750  | 0.4934          | 36.7385 |
| 0.0832        | 3.37  | 800  | 0.4796          | 34.3641 |
| 0.0782        | 3.58  | 850  | 0.4742          | 39.5270 |
| 0.0724        | 3.79  | 900  | 0.4634          | 42.7388 |
| 0.0733        | 4.0   | 950  | 0.4544          | 38.6987 |
| 0.0409        | 4.21  | 1000 | 0.4778          | 33.1953 |
| 0.0437        | 4.42  | 1050 | 0.4584          | 33.3793 |
| 0.036         | 4.63  | 1100 | 0.4476          | 33.9223 |
| 0.0321        | 4.84  | 1150 | 0.4538          | 32.0725 |
| 0.0257        | 5.05  | 1200 | 0.4390          | 37.2538 |
| 0.0133        | 5.26  | 1250 | 0.4319          | 30.7289 |
| 0.0104        | 5.47  | 1300 | 0.4065          | 30.5264 |
| 0.0122        | 5.68  | 1350 | 0.4012          | 28.5754 |
| 0.0071        | 5.89  | 1400 | 0.4113          | 28.4925 |
| 0.0038        | 6.11  | 1450 | 0.3939          | 26.8820 |
| 0.0019        | 6.32  | 1500 | 0.3960          | 26.8820 |
| 0.0021        | 6.53  | 1550 | 0.3978          | 27.1305 |
| 0.0017        | 6.74  | 1600 | 0.3970          | 27.1397 |


### Framework versions

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