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roberta-Self-disclosure-badareas-eval_FeedbackESConv5pp_CARE10pp-sweeps-current
youralien/roberta-Self-disclosure-badareas-eval_FeedbackESConv5pp_CARE10pp-sweeps-current
roberta-Self-disclosure-badareas-eval_FeedbackESConv5pp_CARE10pp-sweeps-current is a text classification model from youralien. 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 11, 2025
- Updated
- Mar 11, 2025
- SHA
- 9f72f816
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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-Self-disclosure-badareas-eval_FeedbackESConv5pp_CARE10pp-sweeps-current
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: 0.0525
- Accuracy: 0.9820
- Precision: 0.7838
- Recall: 0.8286
- F1: 0.8056
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: 1.5021066734744005e-05
- train_batch_size: 16
- 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_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.3227 | 1.0 | 109 | 0.0632 | 0.9551 | 0.0 | 0.0 | 0.0 |
| 0.1297 | 2.0 | 218 | 0.0649 | 0.9782 | 0.7045 | 0.8857 | 0.7848 |
| 0.1211 | 3.0 | 327 | 0.0409 | 0.9692 | 0.6 | 0.9429 | 0.7333 |
| 0.1021 | 4.0 | 436 | 0.0599 | 0.9730 | 0.64 | 0.9143 | 0.7529 |
| 0.0797 | 5.0 | 545 | 0.0907 | 0.9756 | 0.66 | 0.9429 | 0.7765 |
| 0.0746 | 6.0 | 654 | 0.1045 | 0.9730 | 0.6346 | 0.9429 | 0.7586 |
| 0.0607 | 7.0 | 763 | 0.0720 | 0.9820 | 0.7333 | 0.9429 | 0.825 |
| 0.0419 | 8.0 | 872 | 0.0771 | 0.9782 | 0.7045 | 0.8857 | 0.7848 |
| 0.0632 | 9.0 | 981 | 0.0536 | 0.9846 | 0.7949 | 0.8857 | 0.8378 |
| 0.0456 | 10.0 | 1090 | 0.0525 | 0.9820 | 0.7838 | 0.8286 | 0.8056 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 2.21.0
- Tokenizers 0.21.0
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Mar 11, 2025
- Updated
- Mar 11, 2025