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whisper-small-finetuned-telugu – AI Model by heisenberg3376 | AlphaNeural AI
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whisper-small-finetuned-telugu
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
te
Sonal0205/telugu_whisper_asr
openai/whisper-small
finetune
apache-2.0
model-index
endpoints_compatible
us
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Model card
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TRY IT OUT HERE: [
https://colab.research.google.com/drive/13gvcXBnIM6J8q_RPeOQkCTffHU3HMUS7?usp=sharing
]
language:
te license: apache-2.0 base_model: openai/whisper-small tags:
generated_from_trainer datasets:
Sonal0205/telugu_whisper_asr metrics:
wer model-index:
name: Whisper Small te - heisenberg3376 results:
task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: telugu asr type: Sonal0205/telugu_whisper_asr args: 'config: te, split: test' metrics:
name: Wer type: wer value: 30.053507728894175
Whisper Small te - heisenberg3376
This model is a fine-tuned version of
openai/whisper-small
on the
Sonal0205/telugu_whisper_asr
dataset. It achieves the following results on the evaluation set:
Loss: 0.1082
Wer: 30.0535
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: 4
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 4000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0923
1.0582
1000
0.1281
43.7277
0.0377
2.1164
2000
0.1060
35.0773
0.0151
3.1746
3000
0.1125
32.5505
0.0063
4.2328
4000
0.1082
30.0535
Framework versions
Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.19.2
Tokenizers 0.19.1
