liqi03's picture
Upload tokenizer
76b8227 verified
metadata
base_model: openai/whisper-large-v3
datasets:
  - google/fleurs
language:
  - tr
license: apache-2.0
metrics:
  - wer
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
model-index:
  - name: Whisper Large V3 tr finetuned 3 - Chee Li
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: Google Fleurs
          type: google/fleurs
          config: tr_tr
          split: None
          args: 'config: tr split: test'
        metrics:
          - type: wer
            value: 33.03861558225648
            name: Wer

Whisper Large V3 tr finetuned 3 - Chee Li

This model is a fine-tuned version of openai/whisper-large-v3 on the Google Fleurs dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1369
  • Wer: 33.0386

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: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0095 5.5866 1000 0.1176 11.7358
0.0003 11.1732 2000 0.1281 33.0462
0.0001 16.7598 3000 0.1347 25.0208
0.0001 22.3464 4000 0.1369 33.0386

Framework versions

  • Transformers 4.42.4
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1