Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Hindi
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Iamth0u/whisper-medium-1_9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Iamth0u/whisper-medium-1_9 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Iamth0u/whisper-medium-1_9")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Iamth0u/whisper-medium-1_9") model = AutoModelForSpeechSeq2Seq.from_pretrained("Iamth0u/whisper-medium-1_9") - Notebooks
- Google Colab
- Kaggle
Whisper Small Hi - Sanchit Gandhi
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: 0.2088
- Wer: 7.0217
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 |
|---|---|---|---|---|
| 0.0284 | 2.1231 | 1000 | 0.1517 | 7.2302 |
| 0.0065 | 4.2463 | 2000 | 0.1786 | 6.9776 |
| 0.0004 | 6.3694 | 3000 | 0.2008 | 6.9856 |
| 0.0003 | 8.4926 | 4000 | 0.2088 | 7.0217 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.0
- Tokenizers 0.21.0
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Model tree for Iamth0u/whisper-medium-1_9
Base model
openai/whisper-smallEvaluation results
- Wer on Common Voice 11.0self-reported7.022