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whisper-medium-konnakol – AI Model by vkunchur19 | AlphaNeural AI
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whisper-medium-konnakol
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
audiofolder
openai/whisper-medium
finetune
apache-2.0
model-index
endpoints_compatible
us
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whisper-medium-konnakol
This model is a fine-tuned version of
openai/whisper-medium
on the audiofolder dataset. It achieves the following results on the evaluation set:
Loss: 0.2686
Wer: 48.1013
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: 2
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
training_steps: 250
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0661
40.0
50
0.2011
49.7890
0.0015
80.0
100
0.2589
48.1013
0.0003
120.0
150
0.2683
48.5232
0.0001
160.0
200
0.2667
48.1013
0.0
200.0
250
0.2686
48.1013
Framework versions
Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1
