distilcamembert-base-ft-AS13_stgdir-100

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pruizf/distilcamembert-base-ft-AS13_stgdir-100

This model is a fine-tuned version of cmarkea/distilcamembert-base on the dataset described below. It achieves the following results on the evaluation set:

• Loss: 0.5002
• Accuracy: 0.8802

Model description

Fine-tuned for stage direction classification in French, using the dataset at https://nakala.fr/10.34847/nkl.fde37ug3.

The categorization scheme and rationale are described in the following publication:

Schneider, Alexia., & Ruiz Fabo, Pablo. (2024). Stage direction classification in French theater: Transfer learning experiments. In Proceedings of the 8th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL 2024) (pp. 278–286). Association for Computational Linguistics. https://aclanthology.org/2024.latechclfl-1.28/

Intended uses & limitations

Stage direction classification in French.

Training and evaluation data

Stage direction dataset annotated with 13 categories by Alexia Schneider & Pablo Ruiz.

The categories were derived from those available at FreDraCor (and originally in the Théâtre Classique platform).

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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 10

Training results

On held-out data:

Training details:

Framework versions

• Transformers 4.57.2
• Pytorch 2.9.0+cu126
• Datasets 4.0.0
• Tokenizers 0.22.1