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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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-
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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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-
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- # xlm-roberta-base-finetuned-panx-de
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-
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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: 0.1386
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- - F1: 0.8627
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-
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- ## Model description
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-
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- More information needed
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-
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- ## Intended uses & limitations
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-
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- More information needed
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-
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- ## Training and evaluation data
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-
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- More information needed
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-
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- ## Training procedure
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-
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- ### Training hyperparameters
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-
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- The following hyperparameters were used during training:
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- - learning_rate: 5e-05
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- - train_batch_size: 24
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- - eval_batch_size: 24
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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: 3
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-
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- ### Training results
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-
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- | Training Loss | Epoch | Step | Validation Loss | F1 |
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- |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 0.2544 | 1.0 | 525 | 0.1504 | 0.8230 |
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- | 0.1277 | 2.0 | 1050 | 0.1416 | 0.8506 |
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- | 0.0796 | 3.0 | 1575 | 0.1386 | 0.8627 |
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-
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-
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- ### Framework versions
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-
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- - Transformers 4.40.2
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- - Pytorch 2.3.0+cpu
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- - Datasets 2.19.1
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- - Tokenizers 0.19.1
 
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+ ---
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+ license: mit
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+ base_model: xlm-roberta-base
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+ tags:
5
+ - generated_from_trainer
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+ metrics:
7
+ - f1
8
+ model-index:
9
+ - name: xlm-roberta-base-finetuned-panx-de
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+ results: []
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+ ---
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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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+
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+ # xlm-roberta-base-finetuned-panx-de
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+
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+ This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on WikiANN (also called PAN-X), a subset of the Cross-lingual TRansfer Evaluation of Multilingual Encoders.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1386
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+ - F1: 0.8627
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
34
+
35
+ ## Training procedure
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+
37
+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 24
42
+ - eval_batch_size: 24
43
+ - 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: 3
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 0.2544 | 1.0 | 525 | 0.1504 | 0.8230 |
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+ | 0.1277 | 2.0 | 1050 | 0.1416 | 0.8506 |
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+ | 0.0796 | 3.0 | 1575 | 0.1386 | 0.8627 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.2
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+ - Pytorch 2.3.0+cpu
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1