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e5_RSE_MultiLabel_08092025
Ludo33/e5_RSE_MultiLabel_08092025
e5_RSE_MultiLabel_08092025 is a text classification model from Ludo33. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- xlm-roberta
- Access
- Public
- Created
- Sep 8, 2025
- Updated
- Sep 25, 2025
- SHA
- 0ca39c1d
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Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
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
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Sep 8, 2025
- Updated
- Sep 25, 2025