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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: None
metrics:
- name: Wer
type: wer
value: 24.28676605926744
---
<!-- 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: 0.3108
- Wer: 24.2868
## 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: 800
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.7157 | 0.21 | 50 | 0.4892 | 42.8216 |
| 0.6314 | 0.42 | 100 | 0.6716 | 58.7153 |
| 0.6187 | 0.63 | 150 | 0.5979 | 47.1195 |
| 0.5396 | 0.84 | 200 | 0.5503 | 45.8126 |
| 0.4857 | 1.05 | 250 | 0.5842 | 42.9873 |
| 0.246 | 1.26 | 300 | 0.5526 | 43.8984 |
| 0.2635 | 1.47 | 350 | 0.4893 | 39.4994 |
| 0.2346 | 1.68 | 400 | 0.4657 | 36.8489 |
| 0.2268 | 1.89 | 450 | 0.4163 | 34.5113 |
| 0.1345 | 2.11 | 500 | 0.4152 | 30.9590 |
| 0.0862 | 2.32 | 550 | 0.4157 | 32.6063 |
| 0.0723 | 2.53 | 600 | 0.3942 | 29.5785 |
| 0.0667 | 2.74 | 650 | 0.3654 | 28.3913 |
| 0.0571 | 2.95 | 700 | 0.3235 | 25.8513 |
| 0.0241 | 3.16 | 750 | 0.3109 | 25.0874 |
| 0.0124 | 3.37 | 800 | 0.3108 | 24.2868 |
### Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.15.0
|