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README.md
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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-it
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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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config: PAN-X.it
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split: train
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args: PAN-X.it
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metrics:
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- name: F1
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type: f1
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value: 0.8239638900287238
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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-it
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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: 0.2462
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- F1: 0.8240
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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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| 0.7922 | 1.0 | 70 | 0.3091 | 0.7421 |
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| 0.2842 | 2.0 | 140 | 0.2508 | 0.8013 |
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| 0.1815 | 3.0 | 210 | 0.2462 | 0.8240 |
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### Framework versions
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- Transformers 4.24.0
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- Pytorch 1.13.0+cpu
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- Datasets 1.16.1
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- Tokenizers 0.13.2
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