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--- |
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language: |
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- mn |
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license: mit |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: bloom-NER-fr |
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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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# bloom-NER-fr |
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This model is a fine-tuned version of [roberta-large-mnli](https://huggingface.co/roberta-large-mnli) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2930 |
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- Precision: 0.5423 |
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- Recall: 0.6361 |
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- F1: 0.5854 |
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- Accuracy: 0.9004 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 6 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.7569 | 1.0 | 47 | 0.4836 | 0.3709 | 0.3924 | 0.3813 | 0.8604 | |
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| 0.4348 | 2.0 | 94 | 0.3771 | 0.4395 | 0.5443 | 0.4863 | 0.8687 | |
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| 0.3607 | 3.0 | 141 | 0.3232 | 0.5115 | 0.6086 | 0.5559 | 0.8953 | |
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| 0.2913 | 4.0 | 188 | 0.2918 | 0.5527 | 0.6255 | 0.5868 | 0.8974 | |
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| 0.2602 | 5.0 | 235 | 0.2835 | 0.5485 | 0.6445 | 0.5926 | 0.9028 | |
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| 0.2332 | 6.0 | 282 | 0.2930 | 0.5423 | 0.6361 | 0.5854 | 0.9004 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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