Downloads · 30 days
14
28% of all-time downloads
irplag_unixcoder_ep30_bs16_lr3e-05_l512_s42_ppn_loss
buelfhood/irplag_unixcoder_ep30_bs16_lr3e-05_l512_s42_ppn_loss
irplag_unixcoder_ep30_bs16_lr3e-05_l512_s42_ppn_loss is a text classification model from buelfhood. 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. --
All-time downloads
50
Public
Parameters
126M
504 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors504 MB · 99%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- roberta
- Access
- Public
- Created
- Nov 16, 2025
- Updated
- Nov 16, 2025
- SHA
- d8f5b527
Try a prompt
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. -->
irplag_unixcoder_ep30_bs16_lr3e-05_l512_s42_ppn_loss
This model is a fine-tuned version of microsoft/unixcoder-base-nine on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0003
- Accuracy: 1.0
- Recall: 1.0
- Precision: 1.0
- F1: 1.0
- F Beta Score: 1.0
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: 16
- eval_batch_size: 16
- 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: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1 | F Beta Score |
|---|---|---|---|---|---|---|---|---|
| 0.7436 | 1.0 | 21 | 0.5902 | 0.8116 | 0.8364 | 0.92 | 0.8762 | 0.8604 |
| 0.4641 | 2.0 | 42 | 0.3162 | 0.8261 | 0.7818 | 1.0 | 0.8776 | 0.8381 |
| 0.1779 | 3.0 | 63 | 0.0954 | 0.9710 | 0.9636 | 1.0 | 0.9815 | 0.9745 |
| 0.1057 | 4.0 | 84 | 0.0334 | 0.9855 | 0.9818 | 1.0 | 0.9908 | 0.9873 |
| 0.0727 | 5.0 | 105 | 0.0328 | 0.9855 | 1.0 | 0.9821 | 0.9910 | 0.9944 |
| 0.0076 | 6.0 | 126 | 0.3636 | 0.9710 | 1.0 | 0.9649 | 0.9821 | 0.9889 |
| 0.011 | 7.0 | 147 | 0.0003 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0668 | 8.0 | 168 | 0.0266 | 0.9855 | 1.0 | 0.9821 | 0.9910 | 0.9944 |
| 0.0005 | 9.0 | 189 | 0.1879 | 0.9855 | 1.0 | 0.9821 | 0.9910 | 0.9944 |
| 0.0003 | 10.0 | 210 | 0.2073 | 0.9855 | 1.0 | 0.9821 | 0.9910 | 0.9944 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.8.0+cu128
- Datasets 3.1.0
- Tokenizers 0.21.4
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- apache-2.0
- Created
- Nov 16, 2025
- Updated
- Nov 16, 2025