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whisper-small-eng – AI Model by transd | AlphaNeural AI
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transd
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whisper-small-eng
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-small
finetune
apache-2.0
endpoints_compatible
us
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whisper-small-eng
This model is a fine-tuned version of
openai/whisper-small
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0103
Wer: 0.1763
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: 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: 4000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0001
8.3333
1000
0.0098
0.1763
0.0
16.6667
2000
0.0101
0.1763
0.0
25.0
3000
0.0103
0.1763
0.0
33.3333
4000
0.0103
0.1763
Framework versions
Transformers 4.44.2
Pytorch 2.4.0
Datasets 3.0.0
Tokenizers 0.19.1
