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STL-ethiollm-b-250K-stance
tadiecool29/STL-ethiollm-b-250K-stance
STL-ethiollm-b-250K-stance 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 mit.
should probably proofread and complete it, then remove this comment. --
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Public
Updated Aug 31, 2026
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At a glance
- Library
- transformers
- License
- mit
- Access
- Public
- Created
- Aug 31, 2026
- Updated
- Aug 31, 2026
- SHA
- 5eee946e
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. -->
STL-ethiollm-b-250K-stance
This model is a fine-tuned version of EthioNLP/EthioLLM-b-250K on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9425
- Stance Precision: 0.7252
- Stance Recall: 0.7226
- F1: 0.7233
- Stance Acc: 0.7157
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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Stance Precision | Stance Recall | F1 | Stance Acc |
|---|---|---|---|---|---|---|---|
| 1.1035 | 1.0 | 377 | 0.9533 | 0.6176 | 0.6363 | 0.6155 | 0.6147 |
| 0.8912 | 2.0 | 754 | 0.8004 | 0.6875 | 0.6999 | 0.6916 | 0.6858 |
| 0.7939 | 3.0 | 1131 | 0.7669 | 0.7218 | 0.7180 | 0.7198 | 0.7120 |
| 0.6274 | 4.0 | 1508 | 0.8415 | 0.7096 | 0.7024 | 0.7017 | 0.6945 |
| 0.5487 | 5.0 | 1885 | 0.8475 | 0.7121 | 0.7241 | 0.7094 | 0.7057 |
| 0.4428 | 6.0 | 2262 | 0.8492 | 0.7325 | 0.7354 | 0.7329 | 0.7257 |
| 0.3451 | 7.0 | 2639 | 0.9364 | 0.7347 | 0.7225 | 0.7259 | 0.7170 |
| 0.3735 | 8.0 | 3016 | 0.9327 | 0.7243 | 0.7199 | 0.7211 | 0.7132 |
| 0.3140 | 9.0 | 3393 | 0.9425 | 0.7252 | 0.7226 | 0.7233 | 0.7157 |
Framework versions
- Transformers 5.15.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
- Library
- transformers
- License
- mit
- Created
- Aug 31, 2026
- Updated
- Aug 31, 2026