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Halmultilingual-MiniLMv2-L6-mnli-xnli_finetuned_rm_con
Kuongan/Halmultilingual-MiniLMv2-L6-mnli-xnli_finetuned_rm_con
Halmultilingual-MiniLMv2-L6-mnli-xnli_finetuned_rm_con 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
- Sep 28, 2025
- Updated
- Sep 28, 2025
- SHA
- 8d3f609c
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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. -->
Halmultilingual-MiniLMv2-L6-mnli-xnli_finetuned_rm_con
This model is a fine-tuned version of MoritzLaurer/multilingual-MiniLMv2-L6-mnli-xnli on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7223
- Accuracy: 0.7257
- F1 Macro: 0.7270
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: 5e-06
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
|---|---|---|---|---|---|
| No log | 1.0 | 88 | 1.0857 | 0.3779 | 0.3578 |
| No log | 2.0 | 176 | 0.9439 | 0.5371 | 0.5400 |
| No log | 3.0 | 264 | 0.8541 | 0.6129 | 0.6160 |
| No log | 4.0 | 352 | 0.8159 | 0.6457 | 0.6478 |
| No log | 5.0 | 440 | 0.7920 | 0.6707 | 0.6730 |
| 0.9092 | 6.0 | 528 | 0.7702 | 0.6814 | 0.6830 |
| 0.9092 | 7.0 | 616 | 0.7609 | 0.7007 | 0.7031 |
| 0.9092 | 8.0 | 704 | 0.7559 | 0.6993 | 0.6999 |
| 0.9092 | 9.0 | 792 | 0.7471 | 0.7093 | 0.7111 |
| 0.9092 | 10.0 | 880 | 0.7395 | 0.7064 | 0.7078 |
| 0.9092 | 11.0 | 968 | 0.7337 | 0.7164 | 0.7178 |
| 0.6686 | 12.0 | 1056 | 0.7262 | 0.7157 | 0.7172 |
| 0.6686 | 13.0 | 1144 | 0.7242 | 0.7186 | 0.7199 |
| 0.6686 | 14.0 | 1232 | 0.7246 | 0.7207 | 0.7219 |
| 0.6686 | 15.0 | 1320 | 0.7241 | 0.7207 | 0.7222 |
| 0.6686 | 16.0 | 1408 | 0.7234 | 0.7229 | 0.7237 |
| 0.6686 | 17.0 | 1496 | 0.7249 | 0.7229 | 0.7242 |
| 0.6049 | 18.0 | 1584 | 0.7239 | 0.725 | 0.7267 |
| 0.6049 | 19.0 | 1672 | 0.7217 | 0.725 | 0.7261 |
| 0.6049 | 20.0 | 1760 | 0.7223 | 0.7257 | 0.7270 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Sep 28, 2025
- Updated
- Sep 28, 2025