Downloads · 30 days
0
MTL-afrolm-stance-sentiment
tadiecool29/MTL-afrolm-stance-sentiment
MTL-afrolm-stance-sentiment is a machine learning model from tadiecool29. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as cc-by-4.0.
should probably proofread and complete it, then remove this comment. --
Access
Public
Updated Aug 27, 2026
Parameters
264M
1.1 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors1.1 GB · 99%
At a glance
- Library
- transformers
- License
- cc-by-4.0
- Access
- Public
- Created
- Aug 27, 2026
- Updated
- Aug 27, 2026
- SHA
- b3c1849e
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. -->
MTL-afrolm-stance-sentiment
This model is a fine-tuned version of bonadossou/afrolm_active_learning on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6749
- Stance F1: 0.6942
- Sentiment F1: 0.6628
- F1: 0.6785
- Stance Acc: 0.6870
- Sentiment Acc: 0.6683
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: cosine
- lr_scheduler_warmup_steps: 300
- num_epochs: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Stance F1 | Sentiment F1 | F1 | Stance Acc | Sentiment Acc |
|---|---|---|---|---|---|---|---|---|
| 2.1010 | 1.0 | 402 | 1.9784 | 0.5370 | 0.5372 | 0.5371 | 0.5337 | 0.5611 |
| 1.7083 | 2.0 | 804 | 1.6941 | 0.6281 | 0.6232 | 0.6256 | 0.6197 | 0.6272 |
| 1.5376 | 3.0 | 1206 | 1.6308 | 0.6633 | 0.6523 | 0.6578 | 0.6559 | 0.6621 |
| 1.3404 | 4.0 | 1608 | 1.6672 | 0.6765 | 0.6617 | 0.6691 | 0.6696 | 0.6683 |
| 1.1362 | 5.0 | 2010 | 1.6751 | 0.6865 | 0.6619 | 0.6742 | 0.6796 | 0.6671 |
| 1.0667 | 6.0 | 2412 | 1.6749 | 0.6942 | 0.6628 | 0.6785 | 0.6870 | 0.6683 |
Framework versions
- Transformers 5.15.0
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
- Library
- transformers
- License
- cc-by-4.0
- Created
- Aug 27, 2026
- Updated
- Aug 27, 2026