metadata

license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
datasets:
  - PolyAI/minds14
metrics:
  - wer
model-index:
  - name: whisper-tiny-en-US
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: PolyAI/minds14
          type: PolyAI/minds14
          config: en-US
          split: train[450:]
          args: en-US
        metrics:
          - name: Wer
            type: wer
            value: 0.3435655253837072

whisper-tiny-en-US

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:

Loss: 0.6286
Wer Ortho: 0.3430
Wer: 0.3436

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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 10
training_steps: 225

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
3.2798	0.25	14	0.9783	0.7218	0.6889
0.6283	0.5	28	0.5667	0.4479	0.4427
0.5574	0.75	42	0.5307	0.4812	0.4858
0.501	1.0	56	0.5130	0.3800	0.3813
0.2296	1.25	70	0.5057	0.3479	0.3436
0.2296	1.5	84	0.5515	0.3572	0.3512
0.2207	1.75	98	0.5356	0.3578	0.3530
0.1928	2.0	112	0.5288	0.3226	0.3200
0.0795	2.25	126	0.5532	0.3257	0.3259
0.0651	2.5	140	0.5833	0.3504	0.3512
0.0719	2.75	154	0.5931	0.3467	0.3501
0.0722	3.0	168	0.5994	0.3498	0.3477
0.0231	3.25	182	0.6030	0.3270	0.3264
0.0433	3.5	196	0.6059	0.3214	0.3200
0.0663	3.75	210	0.6262	0.3646	0.3648
0.0396	4.0	224	0.6286	0.3430	0.3436

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.14.3
Tokenizers 0.13.3