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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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- f1 |
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- accuracy |
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model-index: |
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- name: xlm-roberta-base-hin-finetuned |
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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-hin-finetuned |
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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: 0.1533 |
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- F1: 0.7972 |
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- Roc Auc: 0.8712 |
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- Accuracy: 0.77 |
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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: 32 |
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- eval_batch_size: 32 |
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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: cosine |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| |
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| 0.4175 | 1.0 | 109 | 0.3690 | 0.0 | 0.5 | 0.31 | |
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| 0.3344 | 2.0 | 218 | 0.2807 | 0.1111 | 0.5445 | 0.37 | |
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| 0.21 | 3.0 | 327 | 0.2053 | 0.6797 | 0.8067 | 0.68 | |
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| 0.163 | 4.0 | 436 | 0.1533 | 0.7972 | 0.8712 | 0.77 | |
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| 0.1295 | 5.0 | 545 | 0.1884 | 0.7004 | 0.8255 | 0.69 | |
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| 0.1125 | 6.0 | 654 | 0.1590 | 0.7621 | 0.8558 | 0.75 | |
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| 0.0841 | 7.0 | 763 | 0.1770 | 0.7533 | 0.8653 | 0.73 | |
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| 0.0678 | 8.0 | 872 | 0.1517 | 0.7867 | 0.8813 | 0.75 | |
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### Framework versions |
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- Transformers 4.47.0 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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