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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-finetuned-pos |
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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-pos |
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/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: 0.0706 |
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- Precision: 0.9800 |
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- Recall: 0.9808 |
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- F1: 0.9804 |
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- Accuracy: 0.9821 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 5 |
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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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| 0.1627 | 1.0 | 1583 | 0.1289 | 0.9599 | 0.9633 | 0.9616 | 0.9653 | |
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| 0.1009 | 2.0 | 3166 | 0.0931 | 0.9680 | 0.9716 | 0.9698 | 0.9730 | |
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| 0.0705 | 3.0 | 4749 | 0.0766 | 0.9758 | 0.9774 | 0.9766 | 0.9786 | |
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| 0.0536 | 4.0 | 6332 | 0.0697 | 0.9787 | 0.9795 | 0.9791 | 0.9812 | |
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| 0.0419 | 5.0 | 7915 | 0.0706 | 0.9800 | 0.9808 | 0.9804 | 0.9821 | |
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### Framework versions |
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- Transformers 4.27.3 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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