metadata

library_name: transformers
language:
  - en
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
datasets:
  - wwwtwwwt/fineaudio-NewsPolitics
metrics:
  - wer
model-index:
  - name: Whisper Tiny En - NewsPolitics - Social Commentary
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: fineaudio-NewsPolitics-Social Commentary
          type: wwwtwwwt/fineaudio-NewsPolitics
          args: 'config: en, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 52.65511043774045

Whisper Tiny En - NewsPolitics - Social Commentary

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

Loss: 0.9274
Wer: 52.6551

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
0.8927	0.5705	1000	1.0172	59.8874
0.702	1.1409	2000	0.9510	56.5795
0.6797	1.7114	3000	0.9338	55.1387
0.6021	2.2818	4000	0.9274	52.6551

Framework versions

Transformers 4.45.2
Pytorch 2.4.0
Datasets 3.1.0
Tokenizers 0.20.0