Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Indonesian
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use TheRains/cv9-special-batch8-small-concat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheRains/cv9-special-batch8-small-concat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="TheRains/cv9-special-batch8-small-concat")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("TheRains/cv9-special-batch8-small-concat") model = AutoModelForSpeechSeq2Seq.from_pretrained("TheRains/cv9-special-batch8-small-concat") - Notebooks
- Google Colab
- Kaggle
Whisper Small Indonesian
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_9_0 id dataset. It achieves the following results on the evaluation set:
- Loss: 0.2320
- Wer: 12.9009
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: 4
- 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: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6518 | 0.21 | 1000 | 0.3087 | 18.9510 |
| 0.542 | 0.42 | 2000 | 0.2795 | 16.6966 |
| 0.4933 | 0.63 | 3000 | 0.2543 | 14.3041 |
| 0.4943 | 0.85 | 4000 | 0.2435 | 13.5036 |
| 0.2716 | 1.06 | 5000 | 0.2320 | 12.9009 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
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Model tree for TheRains/cv9-special-batch8-small-concat
Base model
openai/whisper-smallEvaluation results
- Wer on mozilla-foundation/common_voice_9_0 idtest set self-reported12.901