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--- |
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library_name: transformers |
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license: mit |
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base_model: xlm-roberta-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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model-index: |
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- name: xlm-roberta-base-swe |
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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-swe |
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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: 0.0786 |
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- Accuracy: 0.8697 |
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- F1 Binary: 0.6679 |
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- Precision: 0.5772 |
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- Recall: 0.7924 |
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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: 3e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 17 |
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- num_epochs: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Binary | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:---------:|:------:| |
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| No log | 1.0 | 178 | 0.1732 | 0.2080 | 0.2900 | 0.1702 | 0.9788 | |
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| No log | 2.0 | 356 | 0.1125 | 0.8410 | 0.6038 | 0.5134 | 0.7331 | |
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| 0.1289 | 3.0 | 534 | 0.1079 | 0.8452 | 0.6335 | 0.5204 | 0.8093 | |
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| 0.1289 | 4.0 | 712 | 0.0786 | 0.8697 | 0.6679 | 0.5772 | 0.7924 | |
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### Framework versions |
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- Transformers 4.48.0 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.1.0 |
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- Tokenizers 0.21.0 |
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