mikr/whisper-audio-concat-test

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Whisper Large-v2 Czech CV11 audio concatenation test

This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/commonvoice11_0 cs dataset. It achieves the following results on the evaluation set:

• —Loss: 0.2563
• —Wer: 8.3774

Model description

First test of audio concatenation few short samples to one training sample together.

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
• —trainbatchsize: 32
• —evalbatchsize: 8
• —seed: 42
• —distributed_type: multi-GPU
• —gradientaccumulationsteps: 2
• —totaltrainbatch_size: 64
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —lrschedulerwarmup_steps: 500
• —training_steps: 5000

Training results

Framework versions

• —Transformers 4.26.0.dev0
• —Pytorch 1.13.0+cu117
• —Datasets 2.7.1.dev0
• —Tokenizers 0.13.2