---
license: other
library_name: peft
tags:
- generated_from_trainer
base_model: deepseek-ai/deepseek-coder-1.3b-base
model-index:
- name: peft-deepseek-code-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. -->

# peft-deepseek-code-lora

This model is a fine-tuned version of [deepseek-ai/deepseek-coder-1.3b-base](https://huggingface.co/deepseek-ai/deepseek-coder-1.3b-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7771

## 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: 0.0005
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 45
- training_steps: 3000

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.869         | 0.0333 | 100  | 0.8371          |
| 0.8608        | 0.0667 | 200  | 0.7918          |
| 0.7746        | 0.1    | 300  | 0.7638          |
| 0.7381        | 0.1333 | 400  | 0.7487          |
| 0.7078        | 0.1667 | 500  | 0.7371          |
| 0.7066        | 0.2    | 600  | 0.7261          |
| 0.6709        | 0.2333 | 700  | 0.7235          |
| 0.6487        | 0.2667 | 800  | 0.7191          |
| 0.6103        | 0.3    | 900  | 0.7196          |
| 0.6109        | 0.3333 | 1000 | 0.7197          |
| 0.5804        | 0.3667 | 1100 | 0.7112          |
| 0.563         | 0.4    | 1200 | 0.7162          |
| 0.5406        | 0.4333 | 1300 | 0.7157          |
| 0.5286        | 0.4667 | 1400 | 0.7256          |
| 0.4839        | 0.5    | 1500 | 0.7208          |
| 0.5268        | 0.5333 | 1600 | 0.7258          |
| 0.4565        | 0.5667 | 1700 | 0.7280          |
| 0.4366        | 0.6    | 1800 | 0.7298          |
| 0.4729        | 0.6333 | 1900 | 0.7393          |
| 0.4451        | 0.6667 | 2000 | 0.7463          |
| 0.4008        | 0.7    | 2100 | 0.7533          |
| 0.3915        | 0.7333 | 2200 | 0.7609          |
| 0.3769        | 0.7667 | 2300 | 0.7601          |
| 0.3776        | 0.8    | 2400 | 0.7671          |
| 0.3896        | 0.8333 | 2500 | 0.7694          |
| 0.3798        | 0.8667 | 2600 | 0.7727          |
| 0.3683        | 0.9    | 2700 | 0.7756          |
| 0.36          | 0.9333 | 2800 | 0.7774          |
| 0.3713        | 0.9667 | 2900 | 0.7769          |
| 0.352         | 1.0    | 3000 | 0.7771          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.14.6
- Tokenizers 0.19.1