metadata

language:
  - th
base_model: openai/whisper-small
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
  - ter
  - chrf
  - cer
  - bleu
  - suber
model-index:
  - name: Whisper Small Thai Lora - Magi Boss
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          config: th
          split: None
          args: 'config: th, split: validation'
        metrics:
          - name: Wer
            type: wer
            value: 1.1186
          - name: Ter
            type: ter
            value: 111.8553
          - name: ChrF
            type: chrf
            value: 66.9454
          - name: CER
            type: cer
            value: 0.2283
          - name: BLEU
            type: bleu
            value: 3.6586
          - name: SubER
            type: suber
            value: 1.1628
pipeline_tag: automatic-speech-recognition
license: apache-2.0
library_name: peft

Whisper Small Thai Lora - Magi Boss

This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset (Training Set 20000 row, Validation Set 500 row). It achieves the following results on the evaluation set:

Loss: 0.8313
WER: 1.1186
TER: 111.8553
ChrF: 66.9454
CER: 0.2283
BLEU: 3.6586
SubER: 1.1628

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 1e-05
train_batch_size: 32
eval_batch_size: 16
seed: 42
optimizer: AdamW
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 25
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Ter	Chrf	Cer	Bleu	SubER
0.1990	0.4	250	0.8732	1.1969	119.6879	65.8239	0.2487	4.2583	1.2745
0.1902	0.8	500	0.8353	1.1232	112.3175	66.5794	0.2430	3.9823	1.1698
0.1873	1	625	0.8313	1.1186	111.8553	66.9454	0.2283	3.6586	1.1628

Framework versions

PEFT 0.12.1.dev0
Transformers 4.45.0.dev0
Pytorch 2.1.2
Datasets 2.20.0
Tokenizers 0.19.1