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results
Laksh-Mendpara/results
results is a text classification model from Laksh-Mendpara. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Feb 22, 2026
- Updated
- Feb 22, 2026
- SHA
- 9d08672c
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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. -->
results
This model is a fine-tuned version of distilbert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2110
- Accuracy: 0.595
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: 5e-05
- train_batch_size: 10
- eval_batch_size: 16
- 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: 100
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.0050 | 0.1562 | 100 | 1.7880 | 0.3731 |
| 1.5534 | 0.3125 | 200 | 1.4013 | 0.4919 |
| 1.3653 | 0.4688 | 300 | 1.3551 | 0.5238 |
| 1.3075 | 0.625 | 400 | 1.3244 | 0.54 |
| 1.3349 | 0.7812 | 500 | 1.2947 | 0.5469 |
| 1.2770 | 0.9375 | 600 | 1.2404 | 0.5456 |
| 1.1652 | 1.0938 | 700 | 1.3225 | 0.5425 |
| 0.9598 | 1.25 | 800 | 1.2530 | 0.5637 |
| 0.9209 | 1.4062 | 900 | 1.2938 | 0.5687 |
| 0.9700 | 1.5625 | 1000 | 1.2150 | 0.57 |
| 0.9724 | 1.7188 | 1100 | 1.2234 | 0.5675 |
| 0.9007 | 1.875 | 1200 | 1.2194 | 0.5713 |
| 0.8538 | 2.0312 | 1300 | 1.2109 | 0.595 |
| 0.5652 | 2.1875 | 1400 | 1.3418 | 0.5787 |
| 0.5980 | 2.3438 | 1500 | 1.3551 | 0.5794 |
| 0.5600 | 2.5 | 1600 | 1.4324 | 0.5863 |
| 0.5926 | 2.6562 | 1700 | 1.3879 | 0.5794 |
| 0.5105 | 2.8125 | 1800 | 1.4221 | 0.5731 |
| 0.6133 | 2.9688 | 1900 | 1.4057 | 0.58 |
| 0.3847 | 3.125 | 2000 | 1.4601 | 0.5737 |
| 0.3171 | 3.2812 | 2100 | 1.5700 | 0.5744 |
| 0.3563 | 3.4375 | 2200 | 1.5884 | 0.5844 |
| 0.2698 | 3.5938 | 2300 | 1.6227 | 0.5825 |
| 0.2940 | 3.75 | 2400 | 1.6997 | 0.5775 |
| 0.3423 | 3.9062 | 2500 | 1.6714 | 0.5887 |
| 0.2651 | 4.0625 | 2600 | 1.6928 | 0.585 |
| 0.1350 | 4.2188 | 2700 | 1.7678 | 0.5781 |
| 0.1871 | 4.375 | 2800 | 1.8173 | 0.5763 |
| 0.1858 | 4.5312 | 2900 | 1.8271 | 0.5813 |
| 0.1923 | 4.6875 | 3000 | 1.8298 | 0.5875 |
| 0.1377 | 4.8438 | 3100 | 1.8490 | 0.5819 |
| 0.1464 | 5.0 | 3200 | 1.8574 | 0.5794 |
Framework versions
- Transformers 5.2.0
- Pytorch 2.10.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Feb 22, 2026
- Updated
- Feb 22, 2026