Downloads · 30 days
9
15% of all-time downloads
e5_Eau_MultiLabel_Simple_v1
Ludo33/e5_Eau_MultiLabel_Simple_v1
e5_Eau_MultiLabel_Simple_v1 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. --
All-time downloads
62
Public
Parameters
560M
9 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors2.2 GB · 99%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- xlm-roberta
- Access
- Public
- Created
- Jul 22, 2025
- Updated
- Jul 22, 2025
- SHA
- 14c7f40e
Try a prompt
Base models
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_Eau_MultiLabel_Simple_v1
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: 0.2282
- F1 Weighted: 0.9103
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: 2e-05
- 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: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Weighted |
|---|---|---|---|---|
| 0.5914 | 1.0 | 148 | 0.3093 | 0.8540 |
| 0.2559 | 2.0 | 296 | 0.2461 | 0.8949 |
| 0.164 | 3.0 | 444 | 0.2225 | 0.9039 |
| 0.1198 | 4.0 | 592 | 0.2282 | 0.9103 |
Framework versions
- Transformers 4.53.2
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.2
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Jul 22, 2025
- Updated
- Jul 22, 2025