---
language:
- mn
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Large MN - Ankhbayasgalan Davaadorj
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 16.1 & FLEURS
      type: mozilla-foundation/common_voice_16_1
      config: mn
      split: None
      args: 'config: mn, split: test+validation'
    metrics:
    - name: Wer
      type: wer
      value: 56.63604862218799
---

<!-- 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 Large MN - Ankhbayasgalan Davaadorj

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the Common Voice 16.1 & FLEURS dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5084
- Wer: 56.6360

## 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: 10
- training_steps: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3906        | 0.6   | 100  | 0.5084          | 56.6360 |


### Framework versions

- Transformers 4.37.2
- Pytorch 1.12.1+cu116
- Datasets 2.17.0
- Tokenizers 0.15.2