Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Slovenian
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use samolego/whisper-small-sl-mozilla with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use samolego/whisper-small-sl-mozilla with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="samolego/whisper-small-sl-mozilla")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("samolego/whisper-small-sl-mozilla") model = AutoModelForSpeechSeq2Seq.from_pretrained("samolego/whisper-small-sl-mozilla") - Notebooks
- Google Colab
- Kaggle
Whisper Small - Slovenian
Note: you'll probably want to use the newer version, trained on Artur1.0 dataset
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: 0.4640
- Wer: 28.2530
Model description
This is a speech-to-text model specialized for Slovenian language.
Intended uses & limitations
More information needed
Training and evaluation data
The dataset used was Common Voice 11.0 from Mozilla. Train and validation sets were merged and tested against test dataset.
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 |
|---|---|---|---|---|
| 0.0125 | 6.06 | 1000 | 0.4145 | 29.7100 |
| 0.0006 | 12.12 | 2000 | 0.4312 | 28.1364 |
| 0.0003 | 18.18 | 3000 | 0.4560 | 28.0927 |
| 0.0003 | 24.24 | 4000 | 0.4640 | 28.2530 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for samolego/whisper-small-sl-mozilla
Base model
openai/whisper-smallEvaluation results
- Wer on Common Voice 11.0self-reported28.253