Hugging Face's logo

arun100
/
whisper-base-id-1

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Indonesian
whisper
whisper-event
generated_from_trainer
Eval Results
Inference Endpoints
Model card Files Metrics Community
whisper-base-id-1 / README.md
arun100's picture
arun100
End of training
555f8bb verified
preview code
|
raw history blame contribute delete
No virus
3.14 kB
metadata
language:
  - id
license: apache-2.0
base_model: openai/whisper-base
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_16_0
metrics:
  - wer
model-index:
  - name: Whisper Base Indonesian
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_16_0 id
          type: mozilla-foundation/common_voice_16_0
          config: id
          split: test
          args: id
        metrics:
          - name: Wer
            type: wer
            value: 26.607783604747446

Whisper Base Indonesian

This model is a fine-tuned version of openai/whisper-base on the mozilla-foundation/common_voice_16_0 id dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4198
  • Wer: 26.6078

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: 5e-07
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • 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
0.8238 4.01 500 0.6400 37.9750
0.6348 9.01 1000 0.5193 32.2477
0.4879 14.0 1500 0.4829 30.7250
0.4518 19.0 2000 0.4645 29.7037
0.4253 23.01 2500 0.4513 28.8757
0.4471 28.01 3000 0.4409 28.0937
0.3713 33.01 3500 0.4347 27.7854
0.3233 38.0 4000 0.4307 27.6382
0.3152 43.0 4500 0.4280 27.5324
0.3152 47.01 5000 0.4245 27.2196
0.333 52.01 5500 0.4227 26.9942
0.257 57.0 6000 0.4217 26.9620
0.25 62.0 6500 0.4214 26.8148
0.2587 66.01 7000 0.4206 26.7550
0.2765 71.01 7500 0.4198 26.6998
0.2664 76.01 8000 0.4198 26.6216
0.223 81.0 8500 0.4199 26.6446
0.2309 86.0 9000 0.4199 26.6538
0.233 90.01 9500 0.4198 26.6078
0.2647 95.01 10000 0.4198 26.6216

Framework versions

  • Transformers 4.37.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.16.2.dev0
  • Tokenizers 0.15.0