e5_Eau_v3

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: 0.0705
• Accuracy: 0.9745
• F1: 0.9749

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-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• 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: 100
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.5263	0.9942	86	0.1482	0.9487	0.9493
0.1935	1.9942	172	0.1506	0.9495	0.9499
0.1538	2.9942	258	0.0885	0.9692	0.9694
0.1279	3.9942	344	0.0759	0.9739	0.9737
0.1082	4.9942	430	0.0570	0.9772	0.9772
0.1231	5.9942	516	0.0522	0.9777	0.9778
0.093	6.9942	602	0.0546	0.9770	0.9771
0.0709	7.9942	688	0.0705	0.9745	0.9749

Framework versions

• Transformers 4.51.3
• Pytorch 2.6.0+cu124
• Datasets 3.5.0
• Tokenizers 0.21.1