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metadata
library_name: transformers
license: mit
base_model: intfloat/multilingual-e5-large-instruct
tags:
  - generated_from_trainer
model-index:
  - name: e5_RSE_MultiLabel_08092025
    results: []

e5_RSE_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: 0.2425
  • F1 Weighted: 0.8843

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: 3e-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: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss F1 Weighted
1.0829 1.0 178 0.8684 0.5980
0.8123 2.0 356 0.5814 0.6966
0.6025 3.0 534 0.4584 0.7583
0.4907 4.0 712 0.3871 0.7954
0.422 5.0 890 0.3562 0.8068
0.3762 6.0 1068 0.3218 0.8299
0.3347 7.0 1246 0.3066 0.8399
0.3032 8.0 1424 0.2843 0.8505
0.2782 9.0 1602 0.2726 0.8592
0.2527 10.0 1780 0.2639 0.8653
0.2352 11.0 1958 0.2632 0.8648
0.2211 12.0 2136 0.2549 0.8717
0.2076 13.0 2314 0.2557 0.8746
0.1963 14.0 2492 0.2467 0.8816
0.1865 15.0 2670 0.2471 0.8808
0.1808 16.0 2848 0.2471 0.8829
0.1755 17.0 3026 0.2391 0.8873
0.1723 18.0 3204 0.2404 0.8853
0.1665 19.0 3382 0.2434 0.8848
0.1643 20.0 3560 0.2425 0.8843

Framework versions

  • Transformers 4.56.1
  • Pytorch 2.8.0+cu126
  • Datasets 4.0.0
  • Tokenizers 0.22.0