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clinicia-camembert – AI Model by clinic-ai-togo | AlphaNeural AI
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clinicia-camembert
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transformers
safetensors
camembert
text-classification
generated_from_trainer
almanach/camembert-base
finetune
mit
endpoints_compatible
us
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clinicia-camembert
This model is a fine-tuned version of
camembert-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1424
Accuracy: 0.9936
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: 32
eval_batch_size: 32
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 0.1
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
2.1716
1.0
334
1.7162
0.9368
0.8077
2.0
668
0.5911
0.9963
0.3073
3.0
1002
0.2353
0.9936
0.1987
4.0
1336
0.1424
0.9936
Framework versions
Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
