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librispeech_whisper_small – AI Model by mosesdaudu | AlphaNeural AI
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librispeech_whisper_small
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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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uncombined_audio
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: 0.3756
Wer: 7.5695
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: 8
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: 10
training_steps: 100
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
1.9424
0.16
20
0.7259
11.6499
0.6281
0.32
40
0.5324
9.5801
0.45
0.48
60
0.4571
9.4027
0.4442
0.64
80
0.4031
8.2791
0.3753
0.8
100
0.3756
7.5695
Framework versions
Transformers 4.40.0.dev0
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2
