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Whisper-Anuj-small-Malyalam-final – AI Model by Anujgr8 | AlphaNeural AI
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Whisper-Anuj-small-Malyalam-final
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-small
finetune
apache-2.0
endpoints_compatible
us
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Whisper-Anuj-small-Malyalam-final
This model is a fine-tuned version of
openai/whisper-small
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1640
Wer: 45.0607
Cer: 9.4661
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: 6
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 24
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 1800
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
Cer
0.0563
4.3243
600
0.1279
55.3846
12.5049
0.006
8.6486
1200
0.1527
48.6640
10.2313
0.0004
12.9730
1800
0.1640
45.0607
9.4661
Framework versions
Transformers 4.42.4
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1
