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update model card README.md

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  ---
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  license: mit
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- base_model: xlm-roberta-base
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  tags:
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  - generated_from_trainer
 
 
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  metrics:
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  - f1
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  model-index:
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  - name: xlm-roberta-base-finetuned-panx-de
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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
@@ -15,10 +27,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # xlm-roberta-base-finetuned-panx-de
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- This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1361
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- - F1: 0.8647
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 0.2595 | 1.0 | 525 | 0.1540 | 0.8302 |
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- | 0.1265 | 2.0 | 1050 | 0.1493 | 0.8468 |
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- | 0.0806 | 3.0 | 1575 | 0.1361 | 0.8647 |
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  ### Framework versions
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- - Transformers 4.34.0
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- - Pytorch 2.0.1+cu118
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- - Tokenizers 0.14.1
 
 
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  ---
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  license: mit
 
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  tags:
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  - generated_from_trainer
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+ datasets:
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+ - xtreme
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  metrics:
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  - f1
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  model-index:
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  - name: xlm-roberta-base-finetuned-panx-de
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+ results:
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+ - task:
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+ name: Token Classification
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+ type: token-classification
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+ dataset:
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+ name: xtreme
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+ type: xtreme
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+ args: PAN-X.de
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+ metrics:
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+ - name: F1
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+ type: f1
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+ value: 0.8653353814644136
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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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  # xlm-roberta-base-finetuned-panx-de
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+ This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1339
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+ - F1: 0.8653
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 0.2583 | 1.0 | 525 | 0.1596 | 0.8231 |
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+ | 0.1262 | 2.0 | 1050 | 0.1395 | 0.8468 |
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+ | 0.0824 | 3.0 | 1575 | 0.1339 | 0.8653 |
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  ### Framework versions
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+ - Transformers 4.16.2
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 1.16.1
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+ - Tokenizers 0.15.0