metadata

language:
  - en
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
datasets:
  - PolyAI/minds14
metrics:
  - wer
model-index:
  - name: Whisper Tiny en - ld76
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Minds14
          type: PolyAI/minds14
          config: en-US
          split: train
          args: en-US
        metrics:
          - name: Wer
            type: wer
            value: 0.3616212792906903

Whisper Tiny en - ld76

This model is a fine-tuned version of openai/whisper-tiny on the Minds14 dataset. It achieves the following results on the evaluation set:

Loss: 0.8795
Wer Ortho: 0.3577
Wer: 0.3616

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: 8
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 50
training_steps: 2000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.0006	17.54	500	0.7812	0.3419	0.3477
0.0	35.09	1000	0.8306	0.3267	0.3319
0.0	52.63	1500	0.8573	0.3570	0.3610
0.0	70.18	2000	0.8795	0.3577	0.3616

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.14.1
Tokenizers 0.13.3