| --- |
| library_name: transformers |
| license: mit |
| base_model: intfloat/multilingual-e5-base |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: e5_General_2026 |
| 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 |
|
|
| 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: 0.2143 |
| - F1 Weighted: 0.9333 |
|
|
| ## Model description |
|
|
| More information needed |
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|
| ## Intended uses & limitations |
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|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
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|
| ## Training procedure |
|
|
| ### Training hyperparameters |
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|
| 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 | |
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|
| ### Framework versions |
|
|
| - Transformers 5.13.1 |
| - Pytorch 2.11.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
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|
