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job_classifier_xlmroberta
RantiRepo/job_classifier_xlmroberta
job_classifier_xlmroberta is a text classification model from RantiRepo. 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
- Oct 2, 2025
- Updated
- Feb 16, 2026
- SHA
- 6c7ea190
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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. -->
job_classifier_model_v2
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the Job dataset. It achieves the following results on the evaluation set:
- Loss: 0.0491
- Accuracy: 0.9942
- Precision: 0.9930
- Recall: 0.9953
- F1: 0.9942
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.1122 | 1.0 | 859 | 0.0529 | 0.9907 | 0.9930 | 0.9883 | 0.9907 |
| 0.0325 | 2.0 | 1718 | 0.0338 | 0.9953 | 0.9930 | 0.9977 | 0.9953 |
| 0.0088 | 3.0 | 2577 | 0.0491 | 0.9942 | 0.9930 | 0.9953 | 0.9942 |
Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Oct 2, 2025
- Updated
- Feb 16, 2026