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---
language:
- fi
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Large v3 Fine-Tuned Finnish - CommonVoice13
results: []
---
<!-- 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 - CommonVoice13
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3976
- Wer: 21.4246
It achieves the following results on the Test set:
- Eval_Wer: 21.378612184796612
- Eval_NormalizedWer: 18.415004137170175
## 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
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0001 | 0.84 | 50 | 0.4009 | 21.6363 |
| 0.0013 | 1.68 | 100 | 0.3801 | 22.5014 |
| 0.0013 | 2.53 | 150 | 0.3852 | 23.2192 |
| 0.0009 | 3.37 | 200 | 0.3738 | 23.1824 |
| 0.0007 | 4.21 | 250 | 0.3697 | 23.2100 |
| 0.0001 | 5.05 | 300 | 0.3777 | 21.9032 |
| 0.0001 | 5.89 | 350 | 0.3825 | 21.8388 |
| 0.0001 | 6.74 | 400 | 0.3864 | 21.7651 |
| 0.0 | 7.58 | 450 | 0.3895 | 21.6455 |
| 0.0 | 8.42 | 500 | 0.3917 | 21.5351 |
| 0.0 | 9.26 | 550 | 0.3936 | 21.4983 |
| 0.0 | 10.11 | 600 | 0.3951 | 21.4338 |
| 0.0 | 10.95 | 650 | 0.3962 | 21.4338 |
| 0.0 | 11.79 | 700 | 0.3970 | 21.4614 |
| 0.0 | 12.63 | 750 | 0.3975 | 21.4338 |
| 0.0 | 13.47 | 800 | 0.3976 | 21.4246 |
### Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.15.0
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