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whisper-finetuned-2 – AI Model by SahaRobotik | AlphaNeural AI
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whisper-finetuned-2
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tensorboard
safetensors
whisper
whisper-event
generated_from_trainer
automatic-speech-recognition
tr
mozilla-foundation/common_voice_11_0
openai/whisper-medium
finetune
apache-2.0
model-index
us
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Whisper Medium Tr
This model is a fine-tuned version of
openai/whisper-medium
on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.1577
Wer: 11.4187
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: 5e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 10
training_steps: 200
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0027
4.4444
50
0.1648
10.0923
0.0011
8.8889
100
0.1786
12.0531
0.0001
13.3333
150
0.1590
11.3610
0.0
17.7778
200
0.1577
11.4187
Framework versions
Transformers 4.43.2
Pytorch 2.3.1+cu121
Datasets 2.19.2
Tokenizers 0.19.1
