---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: whisper-small-ne-NP
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: ne-NP
      split: test
      args: ne-NP
    metrics:
    - name: Wer
      type: wer
      value: 57.38758029978587
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# whisper-small-ne-NP

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6005
- Wer: 57.3876

## 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: 4
- 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: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.9935        | 0.17  | 100  | 1.3460          | 91.4347 |
| 0.6624        | 0.35  | 200  | 1.0307          | 85.6531 |
| 0.5002        | 0.52  | 300  | 0.8406          | 77.5161 |
| 0.4426        | 0.7   | 400  | 0.7038          | 76.2313 |
| 0.3063        | 0.87  | 500  | 0.5308          | 71.5203 |
| 0.1949        | 1.05  | 600  | 0.5200          | 66.1670 |
| 0.1974        | 1.22  | 700  | 0.5140          | 65.0964 |
| 0.1734        | 1.4   | 800  | 0.4423          | 67.6660 |
| 0.1619        | 1.57  | 900  | 0.4705          | 62.0985 |
| 0.1697        | 1.75  | 1000 | 0.4676          | 67.0236 |
| 0.1536        | 1.92  | 1100 | 0.4441          | 62.7409 |
| 0.0722        | 2.1   | 1200 | 0.4492          | 58.0300 |
| 0.0674        | 2.27  | 1300 | 0.4597          | 59.9572 |
| 0.0766        | 2.45  | 1400 | 0.4720          | 62.3126 |
| 0.0732        | 2.62  | 1500 | 0.4720          | 60.5996 |
| 0.0737        | 2.8   | 1600 | 0.4704          | 61.0278 |
| 0.0833        | 2.97  | 1700 | 0.4711          | 59.7430 |
| 0.0421        | 3.15  | 1800 | 0.5040          | 60.5996 |
| 0.0444        | 3.32  | 1900 | 0.5096          | 62.5268 |
| 0.0343        | 3.5   | 2000 | 0.5276          | 62.5268 |
| 0.0347        | 3.67  | 2100 | 0.5068          | 57.3876 |
| 0.0326        | 3.85  | 2200 | 0.5143          | 59.3148 |
| 0.0219        | 4.02  | 2300 | 0.5225          | 59.3148 |
| 0.0129        | 4.2   | 2400 | 0.5353          | 59.1006 |
| 0.0159        | 4.37  | 2500 | 0.5639          | 56.9593 |
| 0.0168        | 4.55  | 2600 | 0.5303          | 55.8887 |
| 0.0131        | 4.72  | 2700 | 0.5455          | 58.6724 |
| 0.0122        | 4.9   | 2800 | 0.5548          | 56.5310 |
| 0.0035        | 5.07  | 2900 | 0.5661          | 56.7452 |
| 0.0027        | 5.24  | 3000 | 0.5789          | 57.6017 |
| 0.0034        | 5.42  | 3100 | 0.5887          | 59.1006 |
| 0.0047        | 5.59  | 3200 | 0.5853          | 59.9572 |
| 0.0054        | 5.77  | 3300 | 0.5912          | 58.4582 |
| 0.0042        | 5.94  | 3400 | 0.5862          | 59.3148 |
| 0.0013        | 6.12  | 3500 | 0.5935          | 56.7452 |
| 0.001         | 6.29  | 3600 | 0.5991          | 57.3876 |
| 0.0008        | 6.47  | 3700 | 0.6012          | 57.6017 |
| 0.0014        | 6.64  | 3800 | 0.6002          | 57.8158 |
| 0.001         | 6.82  | 3900 | 0.6006          | 57.8158 |
| 0.0013        | 6.99  | 4000 | 0.6005          | 57.3876 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0
- Datasets 2.11.0
- Tokenizers 0.13.3