metadata

language:
  - km
license: apache-2.0
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - openslr
  - google/fleurs
metrics:
  - wer
model-index:
  - name: Whisper Small Khmer - Seanghay Yath
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Google FLEURS
          type: google/fleurs
          config: km_kh
          split: all
        metrics:
          - name: Wer
            type: wer
            value: 1.0704381586245146

Whisper Small Khmer - Seanghay Yath

This model is a fine-tuned version of openai/whisper-small on the Google FLEURS & OpenSLR dataset. It achieves the following results on the evaluation set:

Loss: 0.4484
Wer: 1.0704

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 6.25e-06
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: 800
training_steps: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2052	3.33	1000	0.3582	1.0233
0.0465	6.67	2000	0.3129	1.0105
0.0089	10.0	3000	0.3977	1.0214
0.0016	13.33	4000	0.4484	1.0704

Framework versions

Transformers 4.28.0.dev0
Pytorch 1.12.1
Datasets 2.11.1.dev0
Tokenizers 0.13.3