e5_Biodiversite_MultiLabel_08092025

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: 0.1089
• F1 Weighted: 0.9597

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_FUSED 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
0.9101	1.0	279	0.5111	0.7380
0.4746	2.0	558	0.3218	0.8485
0.3287	3.0	837	0.2521	0.8778
0.2518	4.0	1116	0.2044	0.9006
0.1986	5.0	1395	0.1751	0.9190
0.1587	6.0	1674	0.1576	0.9316
0.1317	7.0	1953	0.1398	0.9408
0.1111	8.0	2232	0.1270	0.9464
0.0929	9.0	2511	0.1237	0.9517
0.0818	10.0	2790	0.1211	0.9528
0.0716	11.0	3069	0.1133	0.9570
0.0649	12.0	3348	0.1089	0.9597

Framework versions

• Transformers 4.56.0
• Pytorch 2.8.0+cu126
• Datasets 4.0.0
• Tokenizers 0.22.0