whisper_finetuned_ver2 – AI Model by GGarri | AlphaNeural AI

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GGarri/
whisper_finetuned_ver2

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automatic-speech-recognition

generated_from_trainer

openai/whisper-small

endpoints_compatible

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whisper_finetuned_ver2

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

Loss: 0.0048
Cer: 0.5262
Wer: 0.4840

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: 32
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: 500
training_steps: 5000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer	Wer
0.0	35.71	1000	0.0047	0.5496	0.5227
0.0001	71.43	2000	0.0048	0.5262	0.4840
0.0	107.14	3000	0.0051	0.5964	0.5615
0.0	142.86	4000	0.0053	0.6080	0.5808
0.0	178.57	5000	0.0054	0.6080	0.5808

Framework versions

Transformers 4.40.0.dev0
Pytorch 2.0.1
Datasets 2.18.0
Tokenizers 0.15.2