---
library_name: transformers
language:
- sw
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_18_0
metrics:
- wer
model-index:
- name: Whisper Small Hi - Sanchit Gandhi
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_18_0
      args: 'config: sw, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 54.080058758722
---

<!-- 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 Hi - Sanchit Gandhi

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9542
- Wer: 54.0801

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer      |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.7988        | 0.2451  | 100  | 1.2849          | 109.6915 |
| 0.8952        | 0.4902  | 200  | 1.1418          | 95.3581  |
| 0.7785        | 0.7353  | 300  | 1.0263          | 94.3665  |
| 0.7053        | 0.9804  | 400  | 0.9466          | 85.3250  |
| 0.5318        | 1.2255  | 500  | 0.9058          | 81.4873  |
| 0.4995        | 1.4706  | 600  | 0.8554          | 66.8638  |
| 0.4802        | 1.7157  | 700  | 0.8245          | 64.1645  |
| 0.4654        | 1.9608  | 800  | 0.7959          | 77.4477  |
| 0.2461        | 2.2059  | 900  | 0.8013          | 66.1440  |
| 0.2342        | 2.4510  | 1000 | 0.7986          | 52.0676  |
| 0.2239        | 2.6961  | 1100 | 0.7772          | 62.4128  |
| 0.2732        | 2.9412  | 1200 | 0.7743          | 68.8065  |
| 0.1017        | 3.1863  | 1300 | 0.8005          | 65.6739  |
| 0.1081        | 3.4314  | 1400 | 0.8069          | 68.5678  |
| 0.1045        | 3.6765  | 1500 | 0.8008          | 63.2317  |
| 0.1076        | 3.9216  | 1600 | 0.7981          | 70.0220  |
| 0.0604        | 4.1667  | 1700 | 0.8220          | 57.7194  |
| 0.0449        | 4.4118  | 1800 | 0.8294          | 68.8652  |
| 0.0488        | 4.6569  | 1900 | 0.8347          | 59.0709  |
| 0.0453        | 4.9020  | 2000 | 0.8300          | 67.5468  |
| 0.0224        | 5.1471  | 2100 | 0.8509          | 51.2523  |
| 0.0179        | 5.3922  | 2200 | 0.8573          | 59.6071  |
| 0.0224        | 5.6373  | 2300 | 0.8622          | 50.2828  |
| 0.0218        | 5.8824  | 2400 | 0.8650          | 59.3720  |
| 0.01          | 6.1275  | 2500 | 0.8657          | 74.6126  |
| 0.0109        | 6.3725  | 2600 | 0.8816          | 64.8843  |
| 0.0095        | 6.6176  | 2700 | 0.8817          | 57.7378  |
| 0.0086        | 6.8627  | 2800 | 0.8824          | 69.1223  |
| 0.0046        | 7.1078  | 2900 | 0.8988          | 58.5861  |
| 0.0037        | 7.3529  | 3000 | 0.9064          | 55.1965  |
| 0.005         | 7.5980  | 3100 | 0.9079          | 65.3654  |
| 0.0048        | 7.8431  | 3200 | 0.8993          | 52.4128  |
| 0.0023        | 8.0882  | 3300 | 0.9158          | 59.9412  |
| 0.0021        | 8.3333  | 3400 | 0.9183          | 55.7363  |
| 0.0022        | 8.5784  | 3500 | 0.9247          | 60.8336  |
| 0.002         | 8.8235  | 3600 | 0.9282          | 60.2644  |
| 0.0017        | 9.0686  | 3700 | 0.9243          | 61.2156  |
| 0.0016        | 9.3137  | 3800 | 0.9308          | 61.0797  |
| 0.0017        | 9.5588  | 3900 | 0.9399          | 52.4091  |
| 0.0014        | 9.8039  | 4000 | 0.9414          | 50.3783  |
| 0.0013        | 10.0490 | 4100 | 0.9440          | 54.8109  |
| 0.0013        | 10.2941 | 4200 | 0.9430          | 58.0353  |
| 0.0013        | 10.5392 | 4300 | 0.9472          | 55.0790  |
| 0.0012        | 10.7843 | 4400 | 0.9470          | 55.8538  |
| 0.0011        | 11.0294 | 4500 | 0.9488          | 56.8454  |
| 0.0011        | 11.2745 | 4600 | 0.9517          | 54.1315  |
| 0.0011        | 11.5196 | 4700 | 0.9530          | 53.8414  |
| 0.0011        | 11.7647 | 4800 | 0.9538          | 54.4583  |
| 0.0011        | 12.0098 | 4900 | 0.9539          | 54.0507  |
| 0.0011        | 12.2549 | 5000 | 0.9542          | 54.0801  |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.1.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1