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Camemberta-Regv2 – AI Model by WissalAlia | AlphaNeural AI
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WissalAlia
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Camemberta-Regv2
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transformers
safetensors
deberta-v2
question-answering
generated_from_trainer
almanach/camembertav2-base-fquad
finetune
mit
endpoints_compatible
us
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Camemberta-Regv2
This model is a fine-tuned version of
almanach/camembertav2-base-fquad
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.5452
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: 2e-05
train_batch_size: 8
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 9
Training results
Training Loss
Epoch
Step
Validation Loss
0.7503
1.0
40
1.4799
0.5866
2.0
80
1.5452
Framework versions
Transformers 4.44.2
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.19.1
