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---
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