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--- |
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library_name: transformers |
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license: mit |
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base_model: intfloat/multilingual-e5-large-instruct |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: e5_RSE_MultiLabel_06082025 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# e5_RSE_MultiLabel_06082025 |
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This model is a fine-tuned version of [intfloat/multilingual-e5-large-instruct](https://huggingface.co/intfloat/multilingual-e5-large-instruct) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1417 |
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- F1 Weighted: 0.9479 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-06 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 15 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 Weighted | |
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|:-------------:|:-----:|:----:|:---------------:|:-----------:| |
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| 0.9065 | 1.0 | 276 | 0.5238 | 0.7205 | |
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| 0.4792 | 2.0 | 552 | 0.3395 | 0.8138 | |
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| 0.3315 | 3.0 | 828 | 0.2634 | 0.8660 | |
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| 0.2536 | 4.0 | 1104 | 0.2347 | 0.8898 | |
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| 0.2039 | 5.0 | 1380 | 0.2079 | 0.9054 | |
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| 0.1671 | 6.0 | 1656 | 0.1819 | 0.9228 | |
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| 0.1403 | 7.0 | 1932 | 0.1779 | 0.9260 | |
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| 0.121 | 8.0 | 2208 | 0.1647 | 0.9340 | |
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| 0.1069 | 9.0 | 2484 | 0.1544 | 0.9404 | |
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| 0.0917 | 10.0 | 2760 | 0.1495 | 0.9456 | |
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| 0.0828 | 11.0 | 3036 | 0.1470 | 0.9461 | |
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| 0.0753 | 12.0 | 3312 | 0.1420 | 0.9481 | |
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| 0.0696 | 13.0 | 3588 | 0.1417 | 0.9479 | |
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### Framework versions |
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- Transformers 4.55.0 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 4.0.0 |
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- Tokenizers 0.21.4 |
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