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whisper-tiny-google – AI Model by manasbasit | AlphaNeural AI
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whisper-tiny-google
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
en
google/fleurs
openai/whisper-tiny
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper Tiny - FLEURS Fine-Tuned
This model is a fine-tuned version of
openai/whisper-tiny
on the FLEURS dataset. It achieves the following results on the evaluation set:
Loss: 0.8013
Wer: 20.1373
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: 2
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH 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: 500
training_steps: 4000
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0001
20.0
1000
0.7258
19.9085
0.0
40.0
2000
0.7710
20.3661
0.0
60.0
3000
0.7930
20.1373
0.0
80.0
4000
0.8013
20.1373
Framework versions
Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.5.1
Tokenizers 0.21.1
