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whisper_tn_hi_v3 – AI Model by harsh024 | AlphaNeural AI
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whisper_tn_hi_v3
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
generated_from_trainer
apache-2.0
endpoints_compatible
us
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whisper_tn_hi_v3
This model is a fine-tuned version of
openai/whisper-tiny
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.5846
Wer: 78.6633
Cer: 293.0339
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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
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: 500
num_epochs: 4
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
Cer
1.6414
1.0
409
0.8810
83.6367
247.9323
0.5322
2.0
818
0.6398
76.073
285.8609
0.3633
3.0
1227
0.5905
70.2743
268.7294
0.2979
4.0
1636
0.5846
78.6633
293.0339
Framework versions
Transformers 4.24.0
Pytorch 1.13.0
Datasets 2.6.1
Tokenizers 0.11.0
