Downloads · 30 days
12
22% of all-time downloads
progpedia19_unixcoder_ep30_bs16_lr1e-05_l512_s42_ppn_loss
buelfhood/progpedia19_unixcoder_ep30_bs16_lr1e-05_l512_s42_ppn_loss
progpedia19_unixcoder_ep30_bs16_lr1e-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
55
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 17, 2025
- Updated
- Nov 17, 2025
- SHA
- 18633e41
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. -->
progpedia19_unixcoder_ep30_bs16_lr1e-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: 0.0073
- Accuracy: 0.9969
- Recall: 1.0
- Precision: 0.9231
- F1: 0.96
- F Beta Score: 0.975
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: 1e-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 |
|---|---|---|---|---|---|---|---|---|
| 0.23 | 1.0 | 94 | 0.1850 | 0.9969 | 0.9167 | 1.0 | 0.9565 | 0.9408 |
| 0.0343 | 2.0 | 188 | 0.1838 | 0.9938 | 0.8333 | 1.0 | 0.9091 | 0.8784 |
| 0.0003 | 3.0 | 282 | 0.3482 | 0.9938 | 0.8333 | 1.0 | 0.9091 | 0.8784 |
| 0.0005 | 4.0 | 376 | 0.1382 | 0.9938 | 0.8333 | 1.0 | 0.9091 | 0.8784 |
| 0.0008 | 5.0 | 470 | 0.0073 | 0.9969 | 1.0 | 0.9231 | 0.96 | 0.975 |
| 0.1033 | 6.0 | 564 | 0.0353 | 0.9938 | 0.9167 | 0.9167 | 0.9167 | 0.9167 |
| 0.0001 | 7.0 | 658 | 0.0606 | 0.9969 | 0.9167 | 1.0 | 0.9565 | 0.9408 |
| 0.0001 | 8.0 | 752 | 0.1278 | 0.9969 | 0.9167 | 1.0 | 0.9565 | 0.9408 |
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 17, 2025
- Updated
- Nov 17, 2025