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djamina
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relatives_psr

Token Classification
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  1. README.md +11 -16
  2. model.safetensors +1 -1
  3. runs/Jun13_00-08-32_1216ae0d394d/events.out.tfevents.1718237352.1216ae0d394d.1847.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -9,11 +9,6 @@ metrics:
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  model-index:
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  - name: relatives_psr
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  results: []
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- datasets:
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- - djamina/relatives_psr
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- language:
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- - fr
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- pipeline_tag: token-classification
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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
@@ -23,11 +18,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0536
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- - Precision: 0.6640
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- - Recall: 0.6450
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- - F1: 0.6483
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- - Accuracy: 0.9804
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 1.0 | 49 | 0.0602 | 0.7398 | 0.6309 | 0.5692 | 0.9769 |
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- | No log | 2.0 | 98 | 0.0583 | 0.6821 | 0.6304 | 0.5952 | 0.9789 |
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- | No log | 3.0 | 147 | 0.0584 | 0.6604 | 0.6098 | 0.5610 | 0.9776 |
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- | No log | 4.0 | 196 | 0.0564 | 0.5868 | 0.6107 | 0.5981 | 0.9761 |
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- | No log | 5.0 | 245 | 0.0536 | 0.6640 | 0.6450 | 0.6483 | 0.9804 |
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  ### Framework versions
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  - Transformers 4.41.2
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  - Pytorch 2.3.0+cu121
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  - Datasets 2.19.2
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- - Tokenizers 0.19.1
 
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  model-index:
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  - name: relatives_psr
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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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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0529
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+ - Precision: 0.6343
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+ - Recall: 0.6546
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+ - F1: 0.6432
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+ - Accuracy: 0.9789
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 49 | 0.0582 | 0.5838 | 0.5942 | 0.5267 | 0.9766 |
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+ | No log | 2.0 | 98 | 0.0570 | 0.6645 | 0.6360 | 0.6064 | 0.9781 |
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+ | No log | 3.0 | 147 | 0.0573 | 0.6458 | 0.6423 | 0.5958 | 0.9779 |
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+ | No log | 4.0 | 196 | 0.0558 | 0.6254 | 0.6647 | 0.6365 | 0.9781 |
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+ | No log | 5.0 | 245 | 0.0529 | 0.6343 | 0.6546 | 0.6432 | 0.9789 |
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  ### Framework versions
 
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  - Transformers 4.41.2
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  - Pytorch 2.3.0+cu121
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  - Datasets 2.19.2
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+ - Tokenizers 0.19.1
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