metadata

library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
datasets:
  - PolyAI/minds14
metrics:
  - wer
model-index:
  - name: whisper-tiny-us_en_bs128
    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: 0.3417945690672963

whisper-tiny-us_en_bs128

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: 0.8372
Wer Ortho: 0.3399
Wer: 0.3418

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: 0.0001
train_batch_size: 128
eval_batch_size: 128
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: 50
training_steps: 500
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.1633	6.25	25	0.5503	0.3177	0.3164
0.0027	12.5	50	0.6676	0.3288	0.3294
0.0011	18.75	75	0.7095	0.3134	0.3182
0.0012	25.0	100	0.7296	0.3196	0.3176
0.0014	31.25	125	0.7460	0.3541	0.3583
0.005	37.5	150	0.7059	0.4405	0.4610
0.0009	43.75	175	0.7803	0.3924	0.3961
0.0004	50.0	200	0.7996	0.3455	0.3512
0.0001	56.25	225	0.8074	0.3411	0.3442
0.0001	62.5	250	0.8146	0.3424	0.3459
0.0001	68.75	275	0.8197	0.3430	0.3459
0.0001	75.0	300	0.8239	0.3399	0.3424
0.0001	81.25	325	0.8274	0.3374	0.3400
0.0001	87.5	350	0.8303	0.3356	0.3383
0.0001	93.75	375	0.8324	0.3368	0.3400
0.0001	100.0	400	0.8341	0.3368	0.3388
0.0001	106.25	425	0.8354	0.3405	0.3424
0.0001	112.5	450	0.8364	0.3399	0.3418
0.0001	118.75	475	0.8371	0.3399	0.3418
0.0001	125.0	500	0.8372	0.3399	0.3418

Framework versions

Transformers 4.46.2
Pytorch 2.5.1+cu124
Datasets 3.1.0
Tokenizers 0.20.3