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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-eng |
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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-eng |
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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: 0.1062 |
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- Accuracy: 0.7383 |
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- F1 Binary: 0.6078 |
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- Precision: 0.4993 |
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- Recall: 0.7765 |
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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: 41 |
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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 | 416 | 0.1130 | 0.5809 | 0.5198 | 0.3709 | 0.8687 | |
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| 0.1321 | 2.0 | 832 | 0.1055 | 0.5584 | 0.5215 | 0.3636 | 0.9217 | |
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| 0.1074 | 3.0 | 1248 | 0.1039 | 0.7265 | 0.5710 | 0.4836 | 0.6970 | |
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| 0.0922 | 4.0 | 1664 | 0.1062 | 0.7383 | 0.6078 | 0.4993 | 0.7765 | |
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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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