Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
camembert-literary-quality-regressor-sigmoid – AI Model by JulesGo | AlphaNeural AI
You can deploy this model and start earning money today!
JulesGo
/
camembert-literary-quality-regressor-sigmoid
like
0
transformers
safetensors
camembert
generated_from_trainer
almanach/camembert-base
finetune
mit
endpoints_compatible
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
camembert-literary-quality-regressor-sigmoid
This model is a fine-tuned version of
camembert-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0085
Mae: 0.2789
Mse: 0.1352
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
Mse
0.0379
1.0
234
0.0201
0.4263
0.3223
0.0156
2.0
468
0.0115
0.3388
0.1833
0.009
3.0
702
0.0085
0.2789
0.1352
Framework versions
Transformers 4.53.1
Pytorch 2.7.1
Datasets 3.6.0
Tokenizers 0.21.2
