relatives_labels-cbert_finetuned – AI Model by djamina | AlphaNeural AI

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djamina/
relatives_labels-cbert_finetuned

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text-classification

generated_from_trainer

almanach/camembert-large

autotrain_compatible

endpoints_compatible

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relatives_labels-cbert_finetuned

This model is a fine-tuned version of camembert/camembert-large on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.6900
Accuracy: 0.5859
Precision: 0.7929
Recall: 0.5
F1: 0.3694

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: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	49	0.7593	0.5859	0.5447	0.5071	0.4105
No log	2.0	98	0.7108	0.5859	0.7929	0.5	0.3694
No log	3.0	147	0.6904	0.5859	0.7929	0.5	0.3694
No log	4.0	196	0.6891	0.5859	0.7929	0.5	0.3694
No log	5.0	245	0.6900	0.5859	0.7929	0.5	0.3694

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.19.2
Tokenizers 0.19.1