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End of training
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README.md
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---
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license: mit
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base_model: FacebookAI/xlm-roberta-base
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: xlm-roberta-base-finetuned-ner
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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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# xlm-roberta-base-finetuned-ner
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This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0533
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- Precision: 0.9431
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- Recall: 0.9740
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- F1: 0.9583
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- Accuracy: 0.9850
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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: 2e-05
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- train_batch_size: 2
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- eval_batch_size: 2
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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 | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.1784 | 1.0 | 4667 | 0.1376 | 0.8521 | 0.9175 | 0.8836 | 0.9580 |
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| 0.1155 | 2.0 | 9334 | 0.0790 | 0.9150 | 0.9636 | 0.9387 | 0.9779 |
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| 0.086 | 3.0 | 14001 | 0.0533 | 0.9431 | 0.9740 | 0.9583 | 0.9850 |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.1.2
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- Datasets 2.19.2
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- Tokenizers 0.19.1
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