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xlmr-stl-base-sentiment
tadiecool29/xlmr-stl-base-sentiment
xlmr-stl-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 Aug 26, 2026
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At a glance
- Library
- transformers
- License
- mit
- Access
- Public
- Created
- Aug 26, 2026
- Updated
- Aug 26, 2026
- SHA
- a559cda7
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. -->
xlmr-stl-base-sentiment
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7501
- Sentiment Precision: 0.7167
- Sentiment Recall: 0.7172
- F1: 0.7158
- Sentiment Acc: 0.7219
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 | Sentiment Precision | Sentiment Recall | F1 | Sentiment Acc |
|---|---|---|---|---|---|---|---|
| 0.8405 | 1.0 | 402 | 0.7856 | 0.6781 | 0.6670 | 0.6586 | 0.6746 |
| 0.7892 | 2.0 | 804 | 0.7083 | 0.7067 | 0.7008 | 0.6979 | 0.6983 |
| 0.6419 | 3.0 | 1206 | 0.7734 | 0.6985 | 0.6871 | 0.6773 | 0.6945 |
| 0.5582 | 4.0 | 1608 | 0.7174 | 0.7142 | 0.7154 | 0.7130 | 0.7182 |
| 0.5676 | 5.0 | 2010 | 0.7412 | 0.7098 | 0.7105 | 0.7091 | 0.7157 |
| 0.5029 | 6.0 | 2412 | 0.7501 | 0.7167 | 0.7172 | 0.7158 | 0.7219 |
Framework versions
- Transformers 5.15.0
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
- Library
- transformers
- License
- mit
- Created
- Aug 26, 2026
- Updated
- Aug 26, 2026