README.md

metadata

license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - google/fleurs
metrics:
  - wer
base_model: openai/whisper-large-v2
model-index:
  - name: Whisper_large_Khmer
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: google/fleurs km_kh
          type: google/fleurs
          config: km_kh
          split: test
        metrics:
          - type: wer
            value: 51.168264538722084
            name: Wer

Whisper_large_Khmer

This model is a fine-tuned version of openai/whisper-large-v2 on the google/fleurs km_kh dataset. It achieves the following results on the evaluation set:

• Loss: 0.5659
• Wer: 51.1683

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: 8
• eval_batch_size: 16
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 2
• total_train_batch_size: 64
• total_eval_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 100
• training_steps: 1000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0002	50.0	500	0.5488	51.5328
0.0001	100.0	1000	0.5659	51.1683

Framework versions

• Transformers 4.25.1
• Pytorch 1.13.0+cu117
• Datasets 2.7.1
• Tokenizers 0.13.2