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lora_finetune
prakharsinghal/lora_finetune
lora_finetune is a text generation model from prakharsinghal. Use it when you need the model to write or continue text. 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
- Task
- Text Generation
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Aug 10, 2025
- Updated
- Aug 13, 2025
- SHA
- 20df025a
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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. -->
lora_finetune
This model is a fine-tuned version of Qwen/Qwen2.5-0.5B-Instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8675
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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- 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
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.8734 | 0.9988 | 1000 | 0.8738 |
| 0.8169 | 1.9968 | 2000 | 0.8689 |
| 0.8325 | 2.9948 | 3000 | 0.8675 |
Framework versions
- PEFT 0.17.0
- Transformers 4.55.0
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.4
- Task
- Text Generation
- Library
- peft
- License
- apache-2.0
- Created
- Aug 10, 2025
- Updated
- Aug 13, 2025