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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: 0.8620945214069894 |
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- task: |
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type: token-classification |
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name: Token Classification |
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dataset: |
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name: xtreme |
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type: xtreme |
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config: PAN-X.de |
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split: test |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.899981559318585 |
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verified: true |
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- name: Precision |
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type: precision |
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value: 0.9009035072102546 |
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verified: true |
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- name: Recall |
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type: recall |
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value: 0.9206610317249744 |
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verified: true |
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- name: F1 |
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type: f1 |
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value: 0.9106751198809252 |
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verified: true |
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- name: loss |
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type: loss |
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value: 0.3754884600639343 |
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verified: true |
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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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# 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: 0.1372 |
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- F1: 0.8621 |
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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: 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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 0.2575 | 1.0 | 525 | 0.1621 | 0.8292 | |
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| 0.1287 | 2.0 | 1050 | 0.1378 | 0.8526 | |
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| 0.0831 | 3.0 | 1575 | 0.1372 | 0.8621 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.3.2 |
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- Tokenizers 0.12.1 |
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