README.md

metadata

library_name: transformers
language:
  - en
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
datasets:
  - wwwtwwwt/fineaudio-Entertainment
metrics:
  - wer
model-index:
  - name: Whisper Tiny En - Entertainment - Game Commentary
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: fineaudio-Entertainment-Game Commentary
          type: wwwtwwwt/fineaudio-Entertainment
          args: 'config: en, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 44.63537366215395

Whisper Tiny En - Entertainment - Game Commentary

This model is a fine-tuned version of openai/whisper-tiny on the fineaudio-Entertainment-Game Commentary dataset. It achieves the following results on the evaluation set:

• Loss: 0.8782
• Wer: 44.6354

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: 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
0.7661	0.5984	1000	0.9245	49.5708
0.5931	1.1969	2000	0.8876	48.4366
0.5748	1.7953	3000	0.8788	44.2101
0.4717	2.3938	4000	0.8782	44.6354

Framework versions

• Transformers 4.46.3
• Pytorch 2.4.0
• Datasets 3.1.0
• Tokenizers 0.20.0