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FT-English-10me – AI Model by Pageee | AlphaNeural AI
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FT-English-10me
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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: 0.6197
Wer: 3.4591
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-07
train_batch_size: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 300
training_steps: 600
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.6138
18.1818
100
0.8199
3.4102
0.5068
36.3636
200
0.7678
3.4367
0.3871
54.5455
300
0.6937
3.4632
0.3179
72.7273
400
0.6497
3.4530
0.277
90.9091
500
0.6270
3.4591
0.2598
109.0909
600
0.6197
3.4591
Framework versions
Transformers 4.41.0.dev0
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1
