---
library_name: peft
license: mit
base_model: deepseek-ai/DeepSeek-R1-Distill-Llama-8B
tags:
- base_model:adapter:deepseek-ai/DeepSeek-R1-Distill-Llama-8B
- lora
- transformers
pipeline_tag: text-generation
model-index:
- name: llama8b-netlist-lora
  results: []
---

<!-- 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. -->

# llama8b-netlist-lora

This model is a fine-tuned version of [deepseek-ai/DeepSeek-R1-Distill-Llama-8B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Llama-8B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7873

## 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: 0.0002
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.1418        | 0.1465 | 50   | 1.1014          |
| 0.9843        | 0.2929 | 100  | 0.9528          |
| 0.8627        | 0.4394 | 150  | 0.9061          |
| 0.8749        | 0.5859 | 200  | 0.8757          |
| 0.8136        | 0.7323 | 250  | 0.8529          |
| 0.8294        | 0.8788 | 300  | 0.8440          |
| 0.7829        | 1.0234 | 350  | 0.8361          |
| 0.747         | 1.1699 | 400  | 0.8230          |
| 0.7567        | 1.3164 | 450  | 0.8226          |
| 0.7579        | 1.4628 | 500  | 0.8138          |
| 0.7387        | 1.6093 | 550  | 0.8079          |
| 0.7744        | 1.7558 | 600  | 0.8008          |
| 0.7494        | 1.9022 | 650  | 0.7939          |
| 0.6829        | 2.0469 | 700  | 0.7967          |
| 0.7044        | 2.1933 | 750  | 0.7945          |
| 0.7144        | 2.3398 | 800  | 0.7925          |
| 0.6889        | 2.4863 | 850  | 0.7894          |
| 0.7095        | 2.6327 | 900  | 0.7882          |
| 0.7064        | 2.7792 | 950  | 0.7878          |
| 0.6854        | 2.9257 | 1000 | 0.7873          |


### Framework versions

- PEFT 0.16.0
- Transformers 4.57.1
- Pytorch 2.6.0+cu124
- Datasets 4.1.1
- Tokenizers 0.22.1