opus-base-E – AI Model by Enpas | AlphaNeural AI | AlphaNeural AI

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Enpas/
opus-base-E

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automatic-speech-recognition

generated_from_trainer

openai/whisper-base

endpoints_compatible

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opus-base

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

Loss: 0.0150
Wer: 12.4260

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: 12
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 2000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0201	0.3668	1000	0.0170	13.7081
0.0193	0.7337	2000	0.0150	12.4260

Framework versions

Transformers 4.41.2
Pytorch 2.1.2
Datasets 2.20.0
Tokenizers 0.19.1