metadata

language:
  - en
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: BANG please be the final one (EN)
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Radio-Modified Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          config: en
          split: test
          args: 'config: en, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 8.821029784785962

BANG please be the final one (EN)

This model is a fine-tuned version of openai/whisper-large-v3 on the Radio-Modified Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

Loss: 0.0395
Wer: 8.8210

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
0.1511	0.25	1000	0.1318	20.4937
0.0685	1.2443	2000	0.0845	12.3199
0.0378	2.2385	3000	0.0557	10.4397
0.0283	3.2328	4000	0.0395	8.8210

Framework versions

Transformers 4.41.1
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1