metadata

library_name: transformers
language:
  - en
license: apache-2.0
base_model: openai/whisper-base
tags:
  - generated_from_trainer
datasets:
  - iFaz/common_voice_17_0_emotion_5k
metrics:
  - wer
model-index:
  - name: whisper-base-en-emo-v1
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 17.0(Emotional Tag)
          type: iFaz/common_voice_17_0_emotion_5k
          args: 'config: bn, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 120.10050251256281

whisper-base-en-emo-v1

This model is a fine-tuned version of openai/whisper-base on the Common Voice 17.0(Emotional Tag) dataset. It achieves the following results on the evaluation set:

Loss: 0.9660
Wer: 120.1005

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: 4
eval_batch_size: 8
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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
0.0074	40.0	1000	0.8128	130.1508
0.0002	80.0	2000	0.9065	114.5729
0.0001	120.0	3000	0.9507	109.0452
0.0001	160.0	4000	0.9660	120.1005

Framework versions

Transformers 4.47.1
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0