Downloads · 30 days
7
37% of all-time downloads
xlmr_immigration_combo15_0
AnonymousCS/xlmr_immigration_combo15_0
xlmr_immigration_combo15_0 is a text classification model from AnonymousCS. 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. --
All-time downloads
19
Public
Parameters
560M
2.3 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors2.2 GB · 99%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- xlm-roberta
- Access
- Public
- Created
- Aug 20, 2025
- Updated
- Aug 20, 2025
- SHA
- 43991bc9
Try a prompt
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. -->
xlmr_immigration_combo15_0
This model is a fine-tuned version of FacebookAI/xlm-roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2936
- Accuracy: 0.9113
- 1-f1: 0.8535
- 1-recall: 0.7761
- 1-precision: 0.9481
- Balanced Acc: 0.8774
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: 1e-05
- train_batch_size: 128
- eval_batch_size: 128
- 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: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
|---|---|---|---|---|---|---|---|---|
| 0.6344 | 1.0 | 25 | 0.6176 | 0.6671 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.4013 | 2.0 | 50 | 0.3130 | 0.8856 | 0.8292 | 0.8340 | 0.8244 | 0.8727 |
| 0.2427 | 3.0 | 75 | 0.2754 | 0.9075 | 0.8442 | 0.7529 | 0.9606 | 0.8687 |
| 0.1977 | 4.0 | 100 | 0.2495 | 0.9062 | 0.8507 | 0.8031 | 0.9043 | 0.8803 |
| 0.2381 | 5.0 | 125 | 0.2475 | 0.9100 | 0.8536 | 0.7876 | 0.9315 | 0.8794 |
| 0.1376 | 6.0 | 150 | 0.2874 | 0.8997 | 0.8539 | 0.8803 | 0.8291 | 0.8949 |
| 0.1385 | 7.0 | 175 | 0.2936 | 0.9113 | 0.8535 | 0.7761 | 0.9481 | 0.8774 |
Framework versions
- Transformers 4.56.0.dev0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Aug 20, 2025
- Updated
- Aug 20, 2025