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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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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-conll2003
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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-conll2003
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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: 0.1579
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- Precision: 0.8794
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- Recall: 0.8745
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- F1: 0.8769
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- Accuracy: 0.9758
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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: 32
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- eval_batch_size: 32
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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: 15
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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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| No log | 1.0 | 430 | 0.1374 | 0.8043 | 0.7966 | 0.8004 | 0.9613 |
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| 0.2862 | 2.0 | 860 | 0.1093 | 0.8384 | 0.8482 | 0.8433 | 0.9695 |
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| 0.1043 | 3.0 | 1290 | 0.1121 | 0.8448 | 0.8556 | 0.8502 | 0.9708 |
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| 0.0689 | 4.0 | 1720 | 0.1094 | 0.8635 | 0.8650 | 0.8643 | 0.9737 |
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| 0.0473 | 5.0 | 2150 | 0.1225 | 0.8665 | 0.8625 | 0.8645 | 0.9736 |
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| 0.0342 | 6.0 | 2580 | 0.1186 | 0.8722 | 0.8730 | 0.8726 | 0.9745 |
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| 0.0245 | 7.0 | 3010 | 0.1292 | 0.8802 | 0.8717 | 0.8759 | 0.9755 |
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| 0.0245 | 8.0 | 3440 | 0.1309 | 0.8832 | 0.8689 | 0.8760 | 0.9749 |
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| 0.0177 | 9.0 | 3870 | 0.1388 | 0.8712 | 0.8717 | 0.8715 | 0.9743 |
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| 0.0135 | 10.0 | 4300 | 0.1466 | 0.8699 | 0.8728 | 0.8714 | 0.9752 |
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| 0.0103 | 11.0 | 4730 | 0.1486 | 0.8716 | 0.8747 | 0.8731 | 0.9756 |
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| 0.0081 | 12.0 | 5160 | 0.1521 | 0.8789 | 0.8736 | 0.8762 | 0.9759 |
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| 0.007 | 13.0 | 5590 | 0.1546 | 0.8804 | 0.8734 | 0.8769 | 0.9756 |
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| 0.0053 | 14.0 | 6020 | 0.1552 | 0.8750 | 0.8732 | 0.8741 | 0.9756 |
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| 0.0053 | 15.0 | 6450 | 0.1579 | 0.8794 | 0.8745 | 0.8769 | 0.9758 |
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### Framework versions
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- Transformers 4.27.0.dev0
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- Pytorch 1.13.1+cu116
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- Datasets 2.8.0
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- Tokenizers 0.13.2
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