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xlm-roberta-base-orm-finetuned
Kuongan/xlm-roberta-base-orm-finetuned
xlm-roberta-base-orm-finetuned is a text classification model from Kuongan. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- xlm-roberta
- Access
- Public
- Created
- Jan 28, 2025
- Updated
- Jan 28, 2025
- SHA
- 8f0df9d3
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Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
xlm-roberta-base-orm-finetuned
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3548
- F1: 0.4488
- Roc Auc: 0.6931
- Accuracy: 0.5087
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.358 | 1.0 | 147 | 0.3575 | 0.0786 | 0.5225 | 0.3171 |
| 0.3248 | 2.0 | 294 | 0.3283 | 0.1009 | 0.5356 | 0.3641 |
| 0.3002 | 3.0 | 441 | 0.3139 | 0.1816 | 0.5677 | 0.4338 |
| 0.2758 | 4.0 | 588 | 0.2968 | 0.2087 | 0.5733 | 0.4390 |
| 0.2252 | 5.0 | 735 | 0.2916 | 0.3080 | 0.6210 | 0.4774 |
| 0.208 | 6.0 | 882 | 0.3036 | 0.3613 | 0.6439 | 0.5035 |
| 0.1856 | 7.0 | 1029 | 0.3072 | 0.4059 | 0.6574 | 0.5244 |
| 0.1731 | 8.0 | 1176 | 0.3202 | 0.4286 | 0.6734 | 0.5035 |
| 0.1529 | 9.0 | 1323 | 0.3290 | 0.4000 | 0.6585 | 0.5122 |
| 0.1251 | 10.0 | 1470 | 0.3258 | 0.4290 | 0.6699 | 0.5017 |
| 0.1321 | 11.0 | 1617 | 0.3239 | 0.4378 | 0.6723 | 0.5035 |
| 0.1206 | 12.0 | 1764 | 0.3433 | 0.4430 | 0.6831 | 0.5105 |
| 0.1014 | 13.0 | 1911 | 0.3508 | 0.4323 | 0.6795 | 0.5087 |
| 0.0975 | 14.0 | 2058 | 0.3548 | 0.4488 | 0.6931 | 0.5087 |
| 0.0753 | 15.0 | 2205 | 0.3533 | 0.4481 | 0.6880 | 0.5 |
| 0.0809 | 16.0 | 2352 | 0.3656 | 0.4427 | 0.6886 | 0.5105 |
| 0.0912 | 17.0 | 2499 | 0.3657 | 0.4369 | 0.6831 | 0.5017 |
| 0.0784 | 18.0 | 2646 | 0.3688 | 0.4435 | 0.6869 | 0.5139 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Jan 28, 2025
- Updated
- Jan 28, 2025