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whisper-tiny-bn – AI Model by ehzawad | AlphaNeural AI
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whisper-tiny-bn
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
hf-asr-leaderboard
generated_from_trainer
bn
mozilla-foundation/common_voice_13_0
apache-2.0
model-index
endpoints_compatible
us
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Whisper tiny by ehzawad
This model is a fine-tuned version of
openai/whisper-tiny
on the Common Voice 13.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.2422
Wer: 75.4095
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: 16
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
0.3593
0.53
1000
0.3717
102.7311
0.2502
1.07
2000
0.2802
81.0367
0.2219
1.6
3000
0.2535
80.8361
0.2069
2.14
4000
0.2422
75.4095
Framework versions
Transformers 4.30.0.dev0
Pytorch 2.0.1+cu117
Datasets 2.12.0
Tokenizers 0.13.3
