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# whisper-small-nep

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the ASR Nepali dataset from openslr.org.
It achieves the following results on the evaluation set:
- Loss: 0.2274
- Wer: 43.7277

## Model description

Finetuned Whisper for Nepali dataset

## Intended uses & limitations

This model is an initial finetuning model for ASR for Nepali language. More training is needed for better model performances

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.093         | 2.5   | 1000 | 0.2274          | 43.7277 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "base_model": "openai/whisper-small", "model-index": [{"name": "whisper-small-nep", "results": []}]}
transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer base_model:openai/whisper-small license:apache-2.0 endpoints_compatible region:us