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whisper-tiny-librispeech – AI Model by FrancescoBonzi | AlphaNeural AI
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whisper-tiny-librispeech
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
hf-asr-leaderboard
generated_from_trainer
en
librispeech
openai/whisper-tiny
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper Tiny English - Francesco Bonzi
This model is a fine-tuned version of
openai/whisper-tiny
on the LibriSpeech ASR dataset. It achieves the following results on the evaluation set:
Loss: 0.1858
Wer: 6.6000
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
0.1884
0.56
1000
0.2044
7.2257
0.1119
1.12
2000
0.1911
6.8510
0.1203
1.68
3000
0.1873
6.6038
0.0832
2.24
4000
0.1858
6.6000
Framework versions
Transformers 4.38.2
Pytorch 2.1.0
Datasets 2.18.0
Tokenizers 0.15.2
