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roberta-base-Maradona
YuvrajSingh9886/roberta-base-Maradona
roberta-base-Maradona is a text classification model from YuvrajSingh9886. Use it when you need a label for a piece of text. 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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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Mar 1, 2025
- Updated
- Oct 7, 2026
- SHA
- 35862a6a
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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. -->
roberta-base-Maradona
This model is a fine-tuned version of FacebookAI/roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2692
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: 0.0002
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.3577 | 0.0962 | 10 | 1.2713 |
| 1.3243 | 0.1923 | 20 | 1.2728 |
| 1.3107 | 0.2885 | 30 | 1.2959 |
| 1.312 | 0.3846 | 40 | 1.2748 |
| 1.3671 | 0.4808 | 50 | 1.3367 |
| 1.3327 | 0.5769 | 60 | 1.3070 |
| 1.3419 | 0.6731 | 70 | 1.3431 |
| 1.3405 | 0.7692 | 80 | 1.2734 |
| 1.2465 | 0.8654 | 90 | 1.2881 |
| 1.3376 | 0.9615 | 100 | 1.2953 |
| 1.2883 | 1.0577 | 110 | 1.2678 |
| 1.3219 | 1.1538 | 120 | 1.2775 |
| 1.2754 | 1.25 | 130 | 1.2876 |
| 1.293 | 1.3462 | 140 | 1.2705 |
| 1.2848 | 1.4423 | 150 | 1.2747 |
| 1.3346 | 1.5385 | 160 | 1.2852 |
| 1.3195 | 1.6346 | 170 | 1.2678 |
| 1.3516 | 1.7308 | 180 | 1.3041 |
| 1.3072 | 1.8269 | 190 | 1.2718 |
| 1.3103 | 1.9231 | 200 | 1.3155 |
| 1.338 | 2.0192 | 210 | 1.2849 |
| 1.3551 | 2.1154 | 220 | 1.2753 |
| 1.3342 | 2.2115 | 230 | 1.3073 |
| 1.3228 | 2.3077 | 240 | 1.2871 |
| 1.335 | 2.4038 | 250 | 1.2732 |
| 1.3218 | 2.5 | 260 | 1.2806 |
| 1.2967 | 2.5962 | 270 | 1.2738 |
| 1.2826 | 2.6923 | 280 | 1.2746 |
| 1.2718 | 2.7885 | 290 | 1.2680 |
| 1.2969 | 2.8846 | 300 | 1.2714 |
| 1.3147 | 2.9808 | 310 | 1.2699 |
| 1.253 | 3.0769 | 320 | 1.2703 |
| 1.3062 | 3.1731 | 330 | 1.2714 |
| 1.303 | 3.2692 | 340 | 1.2708 |
| 1.3001 | 3.3654 | 350 | 1.2814 |
| 1.3067 | 3.4615 | 360 | 1.2780 |
| 1.2818 | 3.5577 | 370 | 1.2708 |
| 1.3128 | 3.6538 | 380 | 1.2702 |
| 1.2715 | 3.75 | 390 | 1.2761 |
| 1.3178 | 3.8462 | 400 | 1.2673 |
| 1.2829 | 3.9423 | 410 | 1.2697 |
| 1.3103 | 4.0385 | 420 | 1.2723 |
| 1.3009 | 4.1346 | 430 | 1.2728 |
| 1.2902 | 4.2308 | 440 | 1.2697 |
| 1.3163 | 4.3269 | 450 | 1.2690 |
| 1.3005 | 4.4231 | 460 | 1.2689 |
| 1.3083 | 4.5192 | 470 | 1.2693 |
| 1.2759 | 4.6154 | 480 | 1.2690 |
| 1.2771 | 4.7115 | 490 | 1.2690 |
| 1.2882 | 4.8077 | 500 | 1.2691 |
| 1.2749 | 4.9038 | 510 | 1.2692 |
| 1.2892 | 5.0 | 520 | 1.2692 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
Released freely — support more experiments like it:
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Mar 1, 2025
- Updated
- Oct 7, 2026