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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_Dechets_MultiLabel_11082025 |
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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_Dechets_MultiLabel_11082025 |
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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: 0.1865 |
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- F1 Weighted: 0.9369 |
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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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| 0.9053 | 1.0 | 181 | 0.5982 | 0.7363 | |
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| 0.5249 | 2.0 | 362 | 0.3559 | 0.8555 | |
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| 0.3522 | 3.0 | 543 | 0.2938 | 0.8827 | |
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| 0.277 | 4.0 | 724 | 0.2611 | 0.9013 | |
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| 0.2244 | 5.0 | 905 | 0.2399 | 0.9118 | |
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| 0.1936 | 6.0 | 1086 | 0.2483 | 0.9133 | |
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| 0.165 | 7.0 | 1267 | 0.2163 | 0.9219 | |
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| 0.1422 | 8.0 | 1448 | 0.1924 | 0.9320 | |
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| 0.1232 | 9.0 | 1629 | 0.1878 | 0.9361 | |
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| 0.1096 | 10.0 | 1810 | 0.1913 | 0.9364 | |
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| 0.0975 | 11.0 | 1991 | 0.1865 | 0.9369 | |
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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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