Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Ludo33/e5_General_09092025 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ludo33/e5_General_09092025 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ludo33/e5_General_09092025")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ludo33/e5_General_09092025") model = AutoModelForSequenceClassification.from_pretrained("Ludo33/e5_General_09092025") - Notebooks
- Google Colab
- Kaggle
e5_General_09092025
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: 0.1482
- F1 Weighted: 0.9357
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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Weighted |
|---|---|---|---|---|
| 0.5242 | 1.0 | 740 | 0.2071 | 0.8922 |
| 0.2044 | 2.0 | 1480 | 0.1610 | 0.9117 |
| 0.1462 | 3.0 | 2220 | 0.1408 | 0.9270 |
| 0.1181 | 4.0 | 2960 | 0.1363 | 0.9310 |
| 0.0974 | 5.0 | 3700 | 0.1393 | 0.9329 |
| 0.0815 | 6.0 | 4440 | 0.1482 | 0.9357 |
Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0
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Model tree for Ludo33/e5_General_09092025
Base model
intfloat/multilingual-e5-large-instruct