Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Hindi
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Iamth0u/whisper-base-1_9_less with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Iamth0u/whisper-base-1_9_less with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Iamth0u/whisper-base-1_9_less")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Iamth0u/whisper-base-1_9_less") model = AutoModelForSpeechSeq2Seq.from_pretrained("Iamth0u/whisper-base-1_9_less") - 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: 0.2134
- Wer: 11.2925
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-06
- 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 |
|---|---|---|---|---|
| 0.2806 | 2.1231 | 1000 | 0.2262 | 11.6694 |
| 0.2598 | 4.2463 | 2000 | 0.2161 | 11.3727 |
| 0.2305 | 6.3694 | 3000 | 0.2138 | 11.3165 |
| 0.2051 | 8.4926 | 4000 | 0.2134 | 11.2925 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
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Model tree for Iamth0u/whisper-base-1_9_less
Base model
openai/whisper-smallEvaluation results
- Wer on Common Voice 11.0self-reported11.292