e5_Dechets_MultiLabel_11082025

This model is a fine-tuned version of intfloat/multilingual-e5-large-instruct on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.1865
• F1 Weighted: 0.9369

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: 5e-06
• train_batch_size: 16
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• 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: 15
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1 Weighted
0.9053	1.0	181	0.5982	0.7363
0.5249	2.0	362	0.3559	0.8555
0.3522	3.0	543	0.2938	0.8827
0.277	4.0	724	0.2611	0.9013
0.2244	5.0	905	0.2399	0.9118
0.1936	6.0	1086	0.2483	0.9133
0.165	7.0	1267	0.2163	0.9219
0.1422	8.0	1448	0.1924	0.9320
0.1232	9.0	1629	0.1878	0.9361
0.1096	10.0	1810	0.1913	0.9364
0.0975	11.0	1991	0.1865	0.9369

Framework versions

• Transformers 4.55.0
• Pytorch 2.6.0+cu124
• Datasets 4.0.0
• Tokenizers 0.21.4