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Deepseek-R1-Distill-Qwen-14B-peft-p-tuning
Kenazin/Deepseek-R1-Distill-Qwen-14B-peft-p-tuning
Deepseek-R1-Distill-Qwen-14B-peft-p-tuning is a machine learning model from Kenazin. 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 mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- mit
- Access
- Public
- Created
- May 15, 2025
- Updated
- May 15, 2025
- SHA
- 06740f7c
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. -->
Deepseek-R1-Distill-Qwen-14B-peft-p-tuning
This model is a fine-tuned version of deepseek-ai/DeepSeek-R1-Distill-Qwen-14B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1008
- Accuracy: 0.9711
- Precision: 0.8926
- Recall: 0.9234
- F1: 0.9077
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: 0.001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- 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_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.2967 | 1.0 | 1477 | 0.1583 | 0.9399 | 0.8841 | 0.7011 | 0.7821 |
| 0.1192 | 2.0 | 2954 | 0.2277 | 0.9216 | 0.9267 | 0.5326 | 0.6764 |
| 0.1061 | 3.0 | 4431 | 0.0979 | 0.9705 | 0.8893 | 0.9234 | 0.9060 |
| 0.0733 | 4.0 | 5908 | 0.0953 | 0.9664 | 0.8953 | 0.8851 | 0.8902 |
| 0.0547 | 5.0 | 7385 | 0.1008 | 0.9711 | 0.8926 | 0.9234 | 0.9077 |
Framework versions
- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1
- Library
- peft
- License
- mit
- Created
- May 15, 2025
- Updated
- May 15, 2025