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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: 0.0743 |
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- Precision: 0.9800 |
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- Recall: 0.9811 |
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- F1: 0.9806 |
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- Accuracy: 0.9817 |
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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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| 0.157 | 1.0 | 1583 | 0.1170 | 0.9616 | 0.9641 | 0.9629 | 0.9671 | |
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| 0.0982 | 2.0 | 3166 | 0.0823 | 0.9740 | 0.9745 | 0.9743 | 0.9766 | |
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| 0.0666 | 3.0 | 4749 | 0.0778 | 0.9767 | 0.9771 | 0.9769 | 0.9786 | |
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| 0.0528 | 4.0 | 6332 | 0.0712 | 0.9793 | 0.9800 | 0.9796 | 0.9810 | |
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| 0.0446 | 5.0 | 7915 | 0.0743 | 0.9800 | 0.9811 | 0.9806 | 0.9817 | |
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### Framework versions |
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- Transformers 4.28.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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