metadata

library_name: transformers
license: apache-2.0
base_model: biodatlab/whisper-th-medium-combined
tags:
  - generated_from_trainer
datasets:
  - common_voice_17_0
metrics:
  - wer
model-index:
  - name: whisper-finetune-th
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_17_0
          type: common_voice_17_0
          config: th
          split: None
          args: th
        metrics:
          - name: Wer
            type: wer
            value: 15.045342636924866

whisper-finetune-th

This model is a fine-tuned version of biodatlab/whisper-th-medium-combined on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:

Loss: 0.1015
Wer: 15.0453
Cer: 3.8830

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: 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: 500
training_steps: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
0.2829	0.4873	1000	0.1345	20.0856	5.3644
0.1548	0.9747	2000	0.1161	17.6348	4.5783
0.1775	1.4620	3000	0.1074	15.9448	4.1193
0.1477	1.9493	4000	0.1015	15.0453	3.8830

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1