Downloads · 30 days
10
17% of all-time downloads
deberta-v3-large-ft-icar-a-v1.3
abdiharyadi/deberta-v3-large-ft-icar-a-v1.3
deberta-v3-large-ft-icar-a-v1.3 is a text classification model from abdiharyadi. 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. --
All-time downloads
60
Public
Parameters
435M
33.1 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors1.7 GB · 99%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- deberta-v2
- Access
- Public
- Created
- Aug 9, 2025
- Updated
- Aug 9, 2025
- SHA
- 46d987e4
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. -->
deberta-v3-large-ft-icar-a-v1.3
This model is a fine-tuned version of microsoft/deberta-v3-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.1576
- Accuracy: 0.8760
- Precision: 0.8372
- Recall: 0.7144
- F1: 0.7350
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-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 3
- 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: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 2.4886 | 1.0 | 871 | 0.7499 | 0.7963 | 0.6199 | 0.6086 | 0.6017 |
| 1.8992 | 2.0 | 1742 | 0.9652 | 0.8469 | 0.6961 | 0.6813 | 0.6877 |
| 1.548 | 3.0 | 2613 | 1.1634 | 0.8484 | 0.8299 | 0.6871 | 0.6986 |
| 1.2239 | 4.0 | 3484 | 1.1407 | 0.8729 | 0.8258 | 0.7136 | 0.7342 |
| 0.8945 | 5.0 | 4355 | 1.1494 | 0.8530 | 0.7620 | 0.7112 | 0.7293 |
| 0.7381 | 6.0 | 5226 | 1.3039 | 0.8499 | 0.7615 | 0.7118 | 0.7206 |
| 0.5129 | 7.0 | 6097 | 1.4266 | 0.8652 | 0.8201 | 0.7121 | 0.7253 |
| 0.4255 | 8.0 | 6968 | 1.5332 | 0.8591 | 0.7777 | 0.7069 | 0.7206 |
| 0.279 | 9.0 | 7839 | 1.5381 | 0.8606 | 0.8104 | 0.7047 | 0.7180 |
| 0.2978 | 10.0 | 8710 | 1.6327 | 0.8622 | 0.7995 | 0.7076 | 0.7218 |
| 0.13 | 11.0 | 9581 | 1.7521 | 0.8729 | 0.8319 | 0.7116 | 0.7297 |
| 0.0562 | 12.0 | 10452 | 2.0256 | 0.8622 | 0.8134 | 0.7106 | 0.7191 |
| 0.0537 | 13.0 | 11323 | 1.9061 | 0.8683 | 0.8211 | 0.7148 | 0.7269 |
| 0.071 | 14.0 | 12194 | 2.1575 | 0.8714 | 0.8270 | 0.7179 | 0.7305 |
| 0.0502 | 15.0 | 13065 | 2.1730 | 0.8591 | 0.8223 | 0.7047 | 0.7136 |
| 0.1456 | 16.0 | 13936 | 2.2140 | 0.8729 | 0.8318 | 0.7145 | 0.7325 |
| 0.1122 | 17.0 | 14807 | 2.3640 | 0.8637 | 0.8189 | 0.7070 | 0.7220 |
| 0.0238 | 18.0 | 15678 | 2.3073 | 0.8683 | 0.8297 | 0.7064 | 0.7222 |
| 0.0762 | 19.0 | 16549 | 2.1576 | 0.8760 | 0.8372 | 0.7144 | 0.7350 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.2
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Created
- Aug 9, 2025
- Updated
- Aug 9, 2025