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idt5_base-silver-standard-lora
Firmansyah-Ibrahim/idt5_base-silver-standard-lora
idt5_base-silver-standard-lora is a machine learning model from Firmansyah-Ibrahim. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- May 7, 2026
- Updated
- May 7, 2026
- SHA
- a538508a
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. -->
idt5_base-silver-standard-lora
This model is a fine-tuned version of muchad/idt5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.9463
- Rouge1: 0.1894
- Rouge2: 0.0
- Rougel: 0.1968
- Rougelsum: 0.1866
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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 39.0609 | 1.0 | 149 | 7.6769 | 6.1515 | 0.1684 | 6.1419 | 6.1546 |
| 30.7822 | 2.0 | 298 | 6.1796 | 0.7179 | 0.0 | 0.7313 | 0.7174 |
| 28.7988 | 3.0 | 447 | 5.9463 | 0.1894 | 0.0 | 0.1968 | 0.1866 |
Framework versions
- PEFT 0.18.1
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2
- Library
- peft
- License
- apache-2.0
- Created
- May 7, 2026
- Updated
- May 7, 2026