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whisper-small-ro-finetuned – AI Model by iRaduS | AlphaNeural AI
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iRaduS
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whisper-small-ro-finetuned
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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-small-ro-finetuned
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: 0.2681
Wer: 24.5531
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: 8
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
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: 100
training_steps: 500
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.8226
0.3086
100
0.8870
32.4815
0.2026
0.6173
200
0.3149
27.9333
0.1947
0.9259
300
0.2813
25.4876
0.0664
1.2346
400
0.2714
24.7018
0.0772
1.5432
500
0.2681
24.5531
Framework versions
Transformers 4.53.2
Pytorch 2.6.0+cu124
Datasets 2.14.4
Tokenizers 0.21.2
