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TunLangModel1.0 – AI Model by Arbi-Houssem | AlphaNeural AI
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Arbi-Houssem
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TunLangModel1.0
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
ar
Arbi-Houssem/comondov
openai/whisper-medium
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper Tunisien
This model is a fine-tuned version of
openai/whisper-medium
on the comondov dataset. It achieves the following results on the evaluation set:
Loss: 1.7085
Wer: 62.7119
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
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 1000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.1296
50.0
200
1.5371
63.0200
0.0012
100.0
400
1.6181
61.4792
0.0005
150.0
600
1.6781
63.3282
0.0004
200.0
800
1.7005
61.9414
0.0003
250.0
1000
1.7085
62.7119
Framework versions
Transformers 4.41.0.dev0
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1
