|
--- |
|
language: |
|
- sv |
|
license: apache-2.0 |
|
tags: |
|
- hf-asr-leaderboard |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper Small - Swedish |
|
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 Small - Swedish |
|
|
|
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/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 |
|
|