Downloads · 30 days
3
7% of all-time downloads
xlm-roberta-sarcasmo
Fer1155453/xlm-roberta-sarcasmo
xlm-roberta-sarcasmo is a text classification model from Fer1155453. 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
43
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
- Jul 18, 2026
- Updated
- Jul 18, 2026
- SHA
- 587909ac
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. -->
xlm-roberta-sarcasmo
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: 0.5846
- F1 Macro: 0.9288
- F1 Weighted: 0.9318
- F1 Binary: 0.9137
- Accuracy: 0.9319
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: 16
- eval_batch_size: 32
- 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
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Weighted | F1 Binary | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.3240 | 1.0 | 764 | 0.3099 | 0.8772 | 0.8820 | 0.8533 | 0.8819 |
| 0.2463 | 2.0 | 1528 | 0.4246 | 0.8775 | 0.8844 | 0.8425 | 0.8874 |
| 0.2655 | 3.0 | 2292 | 0.3020 | 0.9157 | 0.9186 | 0.9011 | 0.9182 |
| 0.1666 | 4.0 | 3056 | 0.2917 | 0.9232 | 0.9267 | 0.9052 | 0.9274 |
| 0.0641 | 5.0 | 3820 | 0.5168 | 0.9167 | 0.9195 | 0.9022 | 0.9192 |
| 0.0459 | 6.0 | 4584 | 0.5230 | 0.9248 | 0.9282 | 0.9079 | 0.9287 |
| 0.0467 | 7.0 | 5348 | 0.5011 | 0.9333 | 0.9362 | 0.9185 | 0.9365 |
| 0.0071 | 8.0 | 6112 | 0.5746 | 0.9219 | 0.9255 | 0.9039 | 0.9260 |
| 0.0139 | 9.0 | 6876 | 0.5985 | 0.9296 | 0.9326 | 0.9143 | 0.9329 |
| 0.0121 | 10.0 | 7640 | 0.5846 | 0.9288 | 0.9318 | 0.9137 | 0.9319 |
Framework versions
- Transformers 5.13.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Jul 18, 2026
- Updated
- Jul 18, 2026