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FT-English-10mb – AI Model by Pageee | AlphaNeural AI
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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: 0.2180
Wer: 4.2581
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: 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: 500
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0142
18.1818
100
0.2208
4.0237
0.0005
36.3636
200
0.2145
4.1583
0.0002
54.5455
300
0.2162
4.2214
0.0001
72.7273
400
0.2175
4.2418
0.0001
90.9091
500
0.2180
4.2581
Framework versions
Transformers 4.41.0.dev0
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1
