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whisper-large-stt4sg – AI Model by matildecs | AlphaNeural AI
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whisper-large-stt4sg
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-large-v2
finetune
apache-2.0
endpoints_compatible
us
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whisper-large-stt4sg
This model is a fine-tuned version of
openai/whisper-large-v2
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.2355
Wer: 15.5402
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
train_batch_size: 16
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
Wer
0.2994
0.0801
1000
0.3001
19.6658
0.2953
0.1602
2000
0.2741
18.0230
0.2638
0.2403
3000
0.2575
17.0951
0.2456
0.3205
4000
0.2421
15.9823
0.2442
0.4006
5000
0.2355
15.5402
Framework versions
Transformers 4.44.1
Pytorch 2.3.1+cu118
Datasets 2.20.0
Tokenizers 0.19.1
