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whisper-small-el – AI Model by M2LabOrg | AlphaNeural AI
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whisper-small-el
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
el
mozilla-foundation/common_voice_11_0
openai/whisper-small
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper small el - 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: 0.5138
Wer: 31.9292
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
0.0025
17.6991
1000
0.4287
32.2460
0.0004
35.3982
2000
0.4778
31.9199
0.0002
53.0973
3000
0.5045
31.8080
0.0002
70.7965
4000
0.5138
31.9292
Framework versions
Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1
