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whisper-marathi-HSBC – AI Model by Sahithinethi | AlphaNeural AI
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Sahithinethi
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whisper-marathi-HSBC
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transformers
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-tiny
finetune
apache-2.0
endpoints_compatible
us
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whisper-marathi-HSBC
This model is a fine-tuned version of
openai/whisper-tiny
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.8263
Wer: 114.79
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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 8
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
training_steps: 500
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
7.6067
0.5
250
0.9027
109.82
5.1338
1.0
500
0.8263
114.79
Framework versions
Transformers 5.12.0
Pytorch 2.11.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
