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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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- f1 |
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model-index: |
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- name: tmpr6kbd572 |
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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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# tmpr6kbd572 |
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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: 0.5683 |
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- Accuracy: 0.8766 |
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- Precision: 0.9064 |
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- Recall: 0.8907 |
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- F1: 0.8985 |
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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: 8 |
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- eval_batch_size: 16 |
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- seed: 1234 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.3981 | 0.9993 | 737 | 0.2998 | 0.8709 | 0.8879 | 0.9035 | 0.8956 | |
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| 0.2632 | 2.0 | 1475 | 0.3388 | 0.8734 | 0.8915 | 0.9035 | 0.8975 | |
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| 0.1902 | 2.9993 | 2212 | 0.4845 | 0.8791 | 0.8917 | 0.9139 | 0.9027 | |
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| 0.1397 | 3.9973 | 2948 | 0.5548 | 0.8823 | 0.8987 | 0.9108 | 0.9047 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.8.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.20.3 |
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