| --- |
| library_name: transformers |
| license: mit |
| base_model: intfloat/multilingual-e5-base |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: e5_General_2026_V2 |
| results: [] |
| --- |
| |
| <!-- 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_General_2026_V2 |
| |
| This model is a fine-tuned version of [intfloat/multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2693 |
| - F1 Weighted: 0.8980 |
| |
| ## 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 | |
| |:-------------:|:-----:|:-----:|:---------------:|:-----------:| |
| | 0.9259 | 1.0 | 1047 | 0.2613 | 0.8027 | |
| | 0.4565 | 2.0 | 2094 | 0.2130 | 0.8427 | |
| | 0.3400 | 3.0 | 3141 | 0.2124 | 0.8579 | |
| | 0.2721 | 4.0 | 4188 | 0.2109 | 0.8694 | |
| | 0.2249 | 5.0 | 5235 | 0.2290 | 0.8845 | |
| | 0.1894 | 6.0 | 6282 | 0.2344 | 0.8825 | |
| | 0.1568 | 7.0 | 7329 | 0.2507 | 0.8949 | |
| | 0.1381 | 8.0 | 8376 | 0.2556 | 0.8937 | |
| | 0.1176 | 9.0 | 9423 | 0.2743 | 0.8974 | |
| | 0.1108 | 10.0 | 10470 | 0.2693 | 0.8980 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.13.1 |
| - Pytorch 2.11.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
| |
