Downloads · 30 days
14
100% of all-time downloads
cross_encoder_AfriE5-Large-instruct
amDANIEL2024/cross_encoder_AfriE5-Large-instruct
cross_encoder_AfriE5-Large-instruct is a text classification model from amDANIEL2024. 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
14
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
- Sep 24, 2026
- Updated
- Sep 24, 2026
- SHA
- 559ca1d3
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. -->
cross_encoder_AfriE5-Large-instruct
This model is a fine-tuned version of McGill-NLP/AfriE5-Large-instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4044
- Accuracy: 0.9398
- F1: 0.9397
- Precision: 0.9417
- Recall: 0.9376
- Auc: 0.9823
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: 64
- 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: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Auc |
|---|---|---|---|---|---|---|---|---|
| 0.5165 | 1.0 | 7484 | 0.4327 | 0.9166 | 0.9160 | 0.9225 | 0.9096 | 0.9727 |
| 0.4368 | 2.0 | 14968 | 0.3652 | 0.9306 | 0.9308 | 0.9277 | 0.934 | 0.9794 |
| 0.2556 | 3.0 | 22452 | 0.4044 | 0.9398 | 0.9397 | 0.9417 | 0.9376 | 0.9823 |
Framework versions
- Transformers 5.17.0
- Pytorch 2.10.0+cu128
- Datasets 5.0.1
- Tokenizers 0.23.2
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Sep 24, 2026
- Updated
- Sep 24, 2026