metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - PolyAI/minds14
metrics:
  - wer
base_model: openai/whisper-tiny
model-index:
  - name: whisper-tiny-asr-english
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: PolyAI/minds14
          type: PolyAI/minds14
          config: en-US
          split: train
          args: en-US
        metrics:
          - type: wer
            value: 0.31582054309327035
            name: Wer

whisper-tiny-asr-english

This model is a fine-tuned version of openai/whisper-tiny on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set:

Wer Ortho: 0.3196
Wer: 0.3158
Loss: 0.5223

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: 4
seed: 42
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: 500

Training results

Training Loss	Epoch	Step	Wer Ortho	Wer	Validation Loss
0.4862	0.89	100	0.3917	0.3719	0.5372
0.3213	1.79	200	0.3769	0.3571	0.4777
0.1822	2.68	300	0.3726	0.3589	0.4746
0.068	3.57	400	0.3276	0.3146	0.4819
0.0333	4.46	500	0.3196	0.3158	0.5223

Framework versions

Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3