metadata

license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
datasets:
  - minds14
metrics:
  - wer
model-index:
  - name: whisper-tiny-finetune-en
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: minds14
          type: minds14
          config: en-US
          split: train
          args: en-US
        metrics:
          - name: Wer
            type: wer
            value: 0.2982021078735276

whisper-tiny-finetune-en

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: 0.5945
Wer Ortho: 0.2999
Wer: 0.2982

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: 16
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
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.4669	0.8929	25	0.5975	0.3205	0.3187
0.3668	1.7857	50	0.5618	0.3044	0.3025
0.3007	2.6786	75	0.5626	0.2967	0.2957
0.1878	3.5714	100	0.5755	0.3096	0.3094
0.1429	4.4643	125	0.5945	0.2999	0.2982

Framework versions

Transformers 4.41.1
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1