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FT-english-10m – AI Model by Pageee | AlphaNeural AI
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FT-english-10m
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
en
librispeech_asr
openai/whisper-small
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper-Small En-10m
This model is a fine-tuned version of
openai/whisper-small
on the librispeech dataset. It achieves the following results on the evaluation set:
Loss: 0.2449
Wer: 3.9340
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: 2e-06
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: 50
training_steps: 200
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.016
16.6667
100
0.2507
3.8973
0.0019
33.3333
200
0.2449
3.9340
Framework versions
Transformers 4.41.0.dev0
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1
