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update model card README.md
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README.md
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---
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language:
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- mn
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license: bigscience-bloom-rail-1.0
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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 [bigscience/bloom-560m](https://huggingface.co/bigscience/bloom-560m) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3194
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- Precision: 0.3970
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- Recall: 0.5804
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- F1: 0.4715
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- Accuracy: 0.9283
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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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| 1.0627 | 1.0 | 235 | 0.3106 | 0.2650 | 0.4111 | 0.3223 | 0.8957 |
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| 0.3001 | 2.0 | 470 | 0.2626 | 0.3603 | 0.5418 | 0.4328 | 0.9145 |
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| 0.2208 | 3.0 | 705 | 0.2848 | 0.3911 | 0.5569 | 0.4595 | 0.9178 |
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| 0.1573 | 4.0 | 940 | 0.2904 | 0.3479 | 0.5336 | 0.4212 | 0.9149 |
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| 0.1004 | 5.0 | 1175 | 0.2746 | 0.3884 | 0.5704 | 0.4621 | 0.9268 |
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| 0.0594 | 6.0 | 1410 | 0.3194 | 0.3970 | 0.5804 | 0.4715 | 0.9283 |
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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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