fsicoli/whisper-large-v3-pt-1000h

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whisper-large-v3-pt-1000h

This model is a fine-tuned version of openai/whisper-large-v3 on the fsicoli/cv17-fleurs-coraa-mls-ted-alcaim-cf-cdc-lapsbm-lapsmail-sydney-lingualibre-voxforge-tatoeba default dataset. It achieves the following results on the evaluation set:

• —Loss: 0.5576
• —Wer: 0.1113

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-06
• —trainbatchsize: 16
• —evalbatchsize: 8
• —seed: 42
• —distributed_type: multi-GPU
• —num_devices: 2
• —totaltrainbatch_size: 32
• —totalevalbatch_size: 16
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —lrschedulerwarmup_steps: 10000
• —training_steps: 82000
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 4.39.0.dev0
• —Pytorch 2.2.1
• —Datasets 2.18.1.dev0
• —Tokenizers 0.15.2