Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Swedish
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use ID2223/whisper-small-swedish with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ID2223/whisper-small-swedish with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ID2223/whisper-small-swedish")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ID2223/whisper-small-swedish") model = AutoModelForSpeechSeq2Seq.from_pretrained("ID2223/whisper-small-swedish") - Notebooks
- Google Colab
- Kaggle
Whisper Small Hi - Group 5
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3281
- Wer: 99.8871
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1485 | 1.29 | 1000 | 0.2993 | 76.5078 |
| 0.0522 | 2.59 | 2000 | 0.2925 | 62.9400 |
| 0.0203 | 3.88 | 3000 | 0.3086 | 93.0118 |
| 0.0045 | 5.17 | 4000 | 0.3281 | 99.8871 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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Model tree for ID2223/whisper-small-swedish
Base model
openai/whisper-smallSpaces using ID2223/whisper-small-swedish 2
Evaluation results
- Wer on Common Voice 11.0test set self-reported99.887