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whisper-small-sr-fleurs – AI Model by Sagicc | AlphaNeural AI
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whisper-small-sr-fleurs
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transformers
pytorch
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
sr
google/fleurs
openai/whisper-small
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper Small Sr Fleurs- Sagicc
This model is a fine-tuned version of
openai/whisper-small
on the Google Fleurs dataset. It achieves the following results on the evaluation set:
Loss: 0.4134
Wer Ortho: 28.9292
Wer: 25.6021
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: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 50
training_steps: 1000
Training results
Training Loss
Epoch
Step
Validation Loss
Wer Ortho
Wer
0.0649
2.49
500
0.3685
30.6352
27.1489
0.0181
4.98
1000
0.4134
28.9292
25.6021
Framework versions
Transformers 4.33.1
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3
