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STL-afroxlmr-base-sentiment
tadiecool29/STL-afroxlmr-base-sentiment
STL-afroxlmr-base-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 mit.
should probably proofread and complete it, then remove this comment. --
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Public
Updated Sep 1, 2026
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At a glance
- Library
- transformers
- License
- mit
- Access
- Public
- Created
- Sep 1, 2026
- Updated
- Sep 1, 2026
- SHA
- 38ba34c6
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-afroxlmr-base-sentiment
This model is a fine-tuned version of Davlan/afro-xlmr-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8290
- Sentiment Precision: 0.7115
- Sentiment Recall: 0.7115
- F1: 0.7113
- Sentiment 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 | Sentiment Precision | Sentiment Recall | F1 | Sentiment Acc |
|---|---|---|---|---|---|---|---|
| 0.7934 | 1.0 | 377 | 0.7107 | 0.7023 | 0.6982 | 0.6995 | 0.7045 |
| 0.6659 | 2.0 | 754 | 0.6630 | 0.7249 | 0.7250 | 0.7177 | 0.7269 |
| 0.5482 | 3.0 | 1131 | 0.6687 | 0.7192 | 0.7215 | 0.7181 | 0.7257 |
| 0.4400 | 4.0 | 1508 | 0.7441 | 0.7226 | 0.7171 | 0.7179 | 0.7195 |
| 0.3982 | 5.0 | 1885 | 0.7949 | 0.7109 | 0.7101 | 0.7081 | 0.7170 |
| 0.2832 | 6.0 | 2262 | 0.8290 | 0.7115 | 0.7115 | 0.7113 | 0.7157 |
Framework versions
- Transformers 5.16.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.23.1
- Library
- transformers
- License
- mit
- Created
- Sep 1, 2026
- Updated
- Sep 1, 2026