---
language:
- mn
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Mn - Sanchit Gandhi
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: mn
      split: None
      args: 'config: mn, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 46.60332022717344
---

<!-- 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 Mn - 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: 0.5062
- Wer: 46.6033

## 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: 2
- 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: 7000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.6115        | 0.4975 | 1000 | 0.7317          | 69.4572 |
| 0.4096        | 0.9950 | 2000 | 0.5577          | 56.7770 |
| 0.2114        | 1.4925 | 3000 | 0.5270          | 52.8506 |
| 0.2126        | 1.9900 | 4000 | 0.4860          | 50.1365 |
| 0.105         | 2.4876 | 5000 | 0.5017          | 48.1542 |
| 0.0678        | 2.9851 | 6000 | 0.4909          | 47.1876 |
| 0.0294        | 3.4826 | 7000 | 0.5062          | 46.6033 |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1