metadata
language:
- sv
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Small - Swedish
results: []
Whisper Small - Swedish
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 & NST dataset. It achieves the following results on the evaluation set:
- Loss: 0.3551
- Wer: 19.2143
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 500
- training_steps: 8000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2128 | 0.85 | 1000 | 0.2955 | 22.1613 |
| 0.0871 | 1.71 | 2000 | 0.2790 | 20.8034 |
| 0.0373 | 2.56 | 3000 | 0.2884 | 19.9269 |
| 0.0163 | 3.41 | 4000 | 0.3082 | 19.5477 |
| 0.0046 | 4.27 | 5000 | 0.3183 | 19.5881 |
| 0.0023 | 5.12 | 6000 | 0.3397 | 19.3757 |
| 0.0023 | 5.97 | 7000 | 0.3468 | 19.3219 |
| 0.0013 | 6.83 | 8000 | 0.3551 | 19.2143 |
Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.12.1
- Datasets 2.7.1
- Tokenizers 0.13.2