Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Marathi
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use simran14/whisper-small-marathi-fine-tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simran14/whisper-small-marathi-fine-tuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="simran14/whisper-small-marathi-fine-tuned")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("simran14/whisper-small-marathi-fine-tuned") model = AutoModelForSpeechSeq2Seq.from_pretrained("simran14/whisper-small-marathi-fine-tuned") - Notebooks
- Google Colab
- Kaggle
simrank14 whisper small marathi fine-tuned
This model is a fine-tuned version of [simran14/mr-small-whisper-oi](https://huggingface.co/simran14/Whisper Small marathi fine-tuned) on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3276
- Wer: 12.7884
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: 5e-06
- train_batch_size: 8
- 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: 100
- training_steps: 3000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0003 | 2.6714 | 3000 | 0.3276 | 12.7884 |
- Downloads last month
- 11
Model tree for simran14/whisper-small-marathi-fine-tuned
Evaluation results
- Wer on Common Voice 11.0test set self-reported12.788