--- base_model: camembert/camembert-large tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: relatives_psr-cbert_finetuned results: [] datasets: - djamina/relatives_psr language: - fr pipeline_tag: token-classification --- # relatives_psr-cbert_finetuned This model is a fine-tuned version of [camembert/camembert-large](https://huggingface.co/camembert/camembert-large) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0532 - Precision: 0.6127 - Recall: 0.5628 - F1: 0.5835 - Accuracy: 0.9789 ## 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 | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | No log | 1.0 | 49 | 0.1420 | 0.9906 | 0.3333 | 0.3286 | 0.9718 | | No log | 2.0 | 98 | 0.0846 | 0.7921 | 0.6010 | 0.5037 | 0.9733 | | No log | 3.0 | 147 | 0.0590 | 0.6117 | 0.5888 | 0.5891 | 0.9782 | | No log | 4.0 | 196 | 0.0555 | 0.6077 | 0.6158 | 0.5861 | 0.9794 | | No log | 5.0 | 245 | 0.0532 | 0.6127 | 0.5628 | 0.5835 | 0.9789 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.3.0+cu121 - Datasets 2.19.2 - Tokenizers 0.19.1