Ludo33/e5_RSE_MultiLabel_11082025

e5_RSE_MultiLabel_06082025

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: 0.1417
• F1 Weighted: 0.9479

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
0.9065	1.0	276	0.5238	0.7205
0.4792	2.0	552	0.3395	0.8138
0.3315	3.0	828	0.2634	0.8660
0.2536	4.0	1104	0.2347	0.8898
0.2039	5.0	1380	0.2079	0.9054
0.1671	6.0	1656	0.1819	0.9228
0.1403	7.0	1932	0.1779	0.9260
0.121	8.0	2208	0.1647	0.9340
0.1069	9.0	2484	0.1544	0.9404
0.0917	10.0	2760	0.1495	0.9456
0.0828	11.0	3036	0.1470	0.9461
0.0753	12.0	3312	0.1420	0.9481
0.0696	13.0	3588	0.1417	0.9479

Framework versions

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