metadata

library_name: transformers
language:
  - ht
license: apache-2.0
base_model: openai/whisper-medium
tags:
  - generated_from_trainer
datasets:
  - phatjmo/cmu_haitian
metrics:
  - wer
model-index:
  - name: Whisper Medium Ht - TranslateLive
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Carnegie Mellon University - Haitian Creole
          type: phatjmo/cmu_haitian
          args: 'config: ht, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 19.04038870331005

Whisper Medium Ht - TranslateLive

This model is a fine-tuned version of openai/whisper-medium on the Carnegie Mellon University - Haitian Creole dataset. It achieves the following results on the evaluation set:

Loss: 0.7836
Wer: 19.0404

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
0.0571	3.4483	1000	0.5976	21.8190
0.0037	6.8966	2000	0.7251	19.5136
0.0003	10.3448	3000	0.7623	19.4807
0.0005	13.7931	4000	0.7836	19.0404

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 3.0.0
Tokenizers 0.19.1