e5_General_2026
This model is a fine-tuned version of intfloat/multilingual-e5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2143
- F1 Weighted: 0.9333
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_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 |
|---|---|---|---|---|
| 0.8639 | 1.0 | 777 | 0.2139 | 0.8930 |
| 0.3767 | 2.0 | 1554 | 0.1821 | 0.9103 |
| 0.2750 | 3.0 | 2331 | 0.1529 | 0.9235 |
| 0.2158 | 4.0 | 3108 | 0.1605 | 0.9231 |
| 0.1740 | 5.0 | 3885 | 0.1749 | 0.9285 |
| 0.1483 | 6.0 | 4662 | 0.1862 | 0.9265 |
| 0.1301 | 7.0 | 5439 | 0.1979 | 0.9299 |
| 0.1052 | 8.0 | 6216 | 0.2072 | 0.9315 |
| 0.0963 | 9.0 | 6993 | 0.2192 | 0.9301 |
| 0.0825 | 10.0 | 7770 | 0.2143 | 0.9333 |
Framework versions
- Transformers 5.13.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2