metadata

license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - google/fleurs
metrics:
  - wer
model-index:
  - name: Whisper_small_Khmer
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: google/fleurs km_kh
          type: google/fleurs
          config: km_kh
          split: test
        metrics:
          - name: Wer
            type: wer
            value: 84.941730294506

Whisper_small_Khmer

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

Loss: 1.9221
Wer: 84.9417

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: 500
training_steps: 2000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.5571	40.0	400	1.2022	89.9564
0.0088	80.0	800	1.7980	86.6669
0.0023	120.0	1200	1.9221	84.9417
0.0002	160.0	1600	2.0559	85.4326
0.0002	200.0	2000	2.0787	85.6536

Framework versions

Transformers 4.25.1
Pytorch 1.13.0+cu117
Datasets 2.7.1
Tokenizers 0.13.2