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distilwhisper_finetune – AI Model by jimjakdiend | AlphaNeural AI

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jimjakdiend/
distilwhisper_finetune

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automatic-speech-recognition

generated_from_trainer

distil-whisper/distil-large-v3

endpoints_compatible

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distilwhisper_finetune

This model is a fine-tuned version of distil-whisper/distil-large-v3 on an unknown dataset. It achieves the following results on the evaluation set:

eval_loss: 0.0432
eval_wer: 3.2604
eval_runtime: 848.1823
eval_samples_per_second: 0.825
eval_steps_per_second: 0.104
epoch: 1.7857
step: 250

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: 20
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
training_steps: 1000
mixed_precision_training: Native AMP

Framework versions

Transformers 4.41.0
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1