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cricket-project-01
rawsun00001/cricket-project-01
cricket-project-01 is a text classification model from rawsun00001. 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
- Apr 14, 2025
- Updated
- Apr 14, 2025
- SHA
- 5172a5e9
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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. -->
cricket-project-01
This model is a fine-tuned version of roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2588
- Accuracy: 0.9361
- Precision: 0.4680
- Recall: 0.5
- F1: 0.4835
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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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: linear
- num_epochs: 7
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.3406 | 0.4318 | 500 | 0.2407 | 0.9361 | 0.4680 | 0.5 | 0.4835 |
| 0.3133 | 0.8636 | 1000 | 0.2432 | 0.9361 | 0.4680 | 0.5 | 0.4835 |
| 0.3181 | 1.2953 | 1500 | 0.2443 | 0.9361 | 0.4680 | 0.5 | 0.4835 |
| 0.3135 | 1.7271 | 2000 | 0.2726 | 0.9361 | 0.4680 | 0.5 | 0.4835 |
| 0.3228 | 2.1589 | 2500 | 0.2730 | 0.9361 | 0.4680 | 0.5 | 0.4835 |
| 0.3226 | 2.5907 | 3000 | 0.2750 | 0.9361 | 0.4680 | 0.5 | 0.4835 |
| 0.3171 | 3.0225 | 3500 | 0.2741 | 0.9361 | 0.4680 | 0.5 | 0.4835 |
| 0.3171 | 3.4542 | 4000 | 0.2625 | 0.9361 | 0.4680 | 0.5 | 0.4835 |
| 0.3056 | 3.8860 | 4500 | 0.2791 | 0.9361 | 0.4680 | 0.5 | 0.4835 |
| 0.3468 | 4.3178 | 5000 | 0.2645 | 0.9361 | 0.4680 | 0.5 | 0.4835 |
| 0.3099 | 4.7496 | 5500 | 0.2540 | 0.9361 | 0.4680 | 0.5 | 0.4835 |
| 0.2992 | 5.1813 | 6000 | 0.2543 | 0.9361 | 0.4680 | 0.5 | 0.4835 |
| 0.3321 | 5.6131 | 6500 | 0.2719 | 0.9361 | 0.4680 | 0.5 | 0.4835 |
| 0.32 | 6.0449 | 7000 | 0.2699 | 0.9361 | 0.4680 | 0.5 | 0.4835 |
| 0.3153 | 6.4767 | 7500 | 0.2643 | 0.9361 | 0.4680 | 0.5 | 0.4835 |
| 0.3278 | 6.9085 | 8000 | 0.2588 | 0.9361 | 0.4680 | 0.5 | 0.4835 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Tokenizers 0.21.1
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Apr 14, 2025
- Updated
- Apr 14, 2025