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whisper-small-sv – AI Model by M2LabOrg | AlphaNeural AI
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whisper-small-sv
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
sv
mozilla-foundation/common_voice_11_0
openai/whisper-small
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper small sv - Michel Mesquita
This model is a fine-tuned version of
openai/whisper-small
on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.4419
Wer: 20.4216
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
gradient_accumulation_steps: 4
total_train_batch_size: 64
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
0.0171
5.1746
1000
0.3474
20.8249
0.0028
10.3493
2000
0.4073
20.1984
0.0011
15.5239
3000
0.4334
20.3947
0.0008
20.6986
4000
0.4419
20.4216
Framework versions
Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.19.2
Tokenizers 0.19.1
