---
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: 31.994939772289754
---

<!-- 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: 0.5662
- Wer: 31.9949

## 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: 0.0001
- 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: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.0691        | 5.99  | 1000  | 0.4597          | 41.5049 |
| 0.0183        | 11.98 | 2000  | 0.4996          | 38.2982 |
| 0.012         | 17.96 | 3000  | 0.5328          | 38.5402 |
| 0.0091        | 23.95 | 4000  | 0.5619          | 38.1277 |
| 0.004         | 29.94 | 5000  | 0.5439          | 35.2236 |
| 0.0019        | 35.93 | 6000  | 0.5731          | 35.3941 |
| 0.001         | 41.92 | 7000  | 0.5309          | 33.3755 |
| 0.0002        | 47.9  | 8000  | 0.5391          | 32.3140 |
| 0.0           | 53.89 | 9000  | 0.5543          | 32.1984 |
| 0.0           | 59.88 | 10000 | 0.5662          | 31.9949 |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2