metadata

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

Whisper Large MN - Ankhbayasgalan Davaadorj

This model is a fine-tuned version of 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