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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_Eau_MultiLabel_08092025 |
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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_Eau_MultiLabel_08092025 |
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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: 0.1092 |
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- F1 Weighted: 0.9588 |
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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_FUSED 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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| 0.8445 | 1.0 | 320 | 0.4706 | 0.7681 | |
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| 0.4237 | 2.0 | 640 | 0.2907 | 0.8595 | |
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| 0.2906 | 3.0 | 960 | 0.2338 | 0.8938 | |
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| 0.2215 | 4.0 | 1280 | 0.1836 | 0.9217 | |
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| 0.179 | 5.0 | 1600 | 0.1627 | 0.9299 | |
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| 0.1513 | 6.0 | 1920 | 0.1523 | 0.9376 | |
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| 0.1266 | 7.0 | 2240 | 0.1457 | 0.9376 | |
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| 0.1101 | 8.0 | 2560 | 0.1351 | 0.9428 | |
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| 0.0965 | 9.0 | 2880 | 0.1199 | 0.9509 | |
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| 0.0873 | 10.0 | 3200 | 0.1175 | 0.9554 | |
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| 0.0767 | 11.0 | 3520 | 0.1180 | 0.9564 | |
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| 0.0707 | 12.0 | 3840 | 0.1092 | 0.9588 | |
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### Framework versions |
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- Transformers 4.56.0 |
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- Pytorch 2.8.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.0 |
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