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  1. README.md +19 -19
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@@ -3,18 +3,18 @@ base_model: MarcBrun/ixambert-finetuned-squad-eu
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  tags:
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  - generated_from_trainer
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  model-index:
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- - name: NeurIXA_From_Ixambert-finetuned-squad-eu
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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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- # NeurIXA_From_Ixambert-finetuned-squad-eu
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  This model is a fine-tuned version of [MarcBrun/ixambert-finetuned-squad-eu](https://huggingface.co/MarcBrun/ixambert-finetuned-squad-eu) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4553
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  ## Model description
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@@ -45,26 +45,26 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | No log | 1.0 | 3 | 4.5910 |
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- | No log | 2.0 | 6 | 3.6086 |
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- | No log | 3.0 | 9 | 3.0027 |
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- | No log | 4.0 | 12 | 2.4933 |
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- | No log | 5.0 | 15 | 2.0479 |
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- | No log | 6.0 | 18 | 1.6777 |
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- | No log | 7.0 | 21 | 1.3752 |
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- | No log | 8.0 | 24 | 1.1311 |
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- | No log | 9.0 | 27 | 0.9425 |
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- | No log | 10.0 | 30 | 0.7820 |
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- | No log | 11.0 | 33 | 0.6559 |
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- | No log | 12.0 | 36 | 0.5652 |
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- | No log | 13.0 | 39 | 0.5052 |
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- | No log | 14.0 | 42 | 0.4691 |
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- | No log | 15.0 | 45 | 0.4553 |
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  ### Framework versions
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  - Transformers 4.37.2
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  - Pytorch 2.3.0
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- - Datasets 2.19.1
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  - Tokenizers 0.15.1
 
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  tags:
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  - generated_from_trainer
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  model-index:
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+ - name: Neurixa_From_Ixambert-finetuned-squad-eu
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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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+ # Neurixa_From_Ixambert-finetuned-squad-eu
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  This model is a fine-tuned version of [MarcBrun/ixambert-finetuned-squad-eu](https://huggingface.co/MarcBrun/ixambert-finetuned-squad-eu) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2018
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | No log | 1.0 | 6 | 4.4728 |
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+ | No log | 2.0 | 12 | 3.3750 |
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+ | No log | 3.0 | 18 | 2.5127 |
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+ | No log | 4.0 | 24 | 1.8246 |
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+ | No log | 5.0 | 30 | 1.3675 |
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+ | No log | 6.0 | 36 | 0.9409 |
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+ | No log | 7.0 | 42 | 0.6393 |
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+ | No log | 8.0 | 48 | 0.4733 |
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+ | No log | 9.0 | 54 | 0.3724 |
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+ | No log | 10.0 | 60 | 0.3093 |
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+ | No log | 11.0 | 66 | 0.2644 |
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+ | No log | 12.0 | 72 | 0.2407 |
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+ | No log | 13.0 | 78 | 0.2161 |
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+ | No log | 14.0 | 84 | 0.2041 |
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+ | No log | 15.0 | 90 | 0.2018 |
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  ### Framework versions
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  - Transformers 4.37.2
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  - Pytorch 2.3.0
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+ - Datasets 2.19.2
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  - Tokenizers 0.15.1