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whisper-small-be2en – AI Model by cobrayyxx | AlphaNeural AI
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whisper-small-be2en
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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-be2en
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: 0.1618
Bleu: 0.9
Chrf: 34.0
Wer: 97.1429
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: 0.0001
train_batch_size: 16
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_ratio: 0.03
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Bleu
Chrf
Wer
2.1697
1.0
1
2.1582
0.47
0.26
117.1429
2.1697
2.0
2
0.2310
0.0
0.0
100.0
0.229
3.0
3
0.1618
0.9
34.0
97.1429
Framework versions
Transformers 4.49.0
Pytorch 2.6.0+cu124
Datasets 3.4.1
Tokenizers 0.21.1
