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camembert-literary-quality-regressor – AI Model by JulesGo | AlphaNeural AI
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JulesGo
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camembert-literary-quality-regressor
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transformers
safetensors
camembert
text-classification
generated_from_trainer
almanach/camembert-base
finetune
mit
autotrain_compatible
endpoints_compatible
us
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camembert-literary-quality-regressor
This model is a fine-tuned version of
camembert-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0409
Mae: 0.1404
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: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Mae
0.2193
1.0
234
0.1520
0.2790
0.028
2.0
468
0.0526
0.1744
0.0179
3.0
702
0.0409
0.1404
Framework versions
Transformers 4.53.1
Pytorch 2.7.1
Datasets 3.6.0
Tokenizers 0.21.2
