---
license: other
library_name: peft
tags:
- generated_from_trainer
base_model: deepseek-ai/deepseek-coder-6.7b-base
model-index:
- name: peft-deepseek-code-lora-7b
  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-7b

This model is a fine-tuned version of [deepseek-ai/deepseek-coder-6.7b-base](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7491

## 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: 8
- eval_batch_size: 8
- 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: 4000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.801         | 0.025 | 100  | 0.7577          |
| 0.7385        | 0.05  | 200  | 0.7172          |
| 0.7535        | 0.075 | 300  | 0.6915          |
| 0.6987        | 0.1   | 400  | 0.6718          |
| 0.6345        | 0.125 | 500  | 0.6596          |
| 0.623         | 0.15  | 600  | 0.6515          |
| 0.6228        | 0.175 | 700  | 0.6413          |
| 0.5966        | 0.2   | 800  | 0.6362          |
| 0.5503        | 0.225 | 900  | 0.6403          |
| 0.504         | 0.25  | 1000 | 0.6274          |
| 0.4782        | 0.275 | 1100 | 0.6270          |
| 0.5021        | 0.3   | 1200 | 0.6272          |
| 0.4737        | 0.325 | 1300 | 0.6190          |
| 0.4343        | 0.35  | 1400 | 0.6233          |
| 0.458         | 0.375 | 1500 | 0.6247          |
| 0.4316        | 0.4   | 1600 | 0.6302          |
| 0.4161        | 0.425 | 1700 | 0.6337          |
| 0.3798        | 0.45  | 1800 | 0.6307          |
| 0.3731        | 0.475 | 1900 | 0.6382          |
| 0.3339        | 0.5   | 2000 | 0.6468          |
| 0.3279        | 0.525 | 2100 | 0.6529          |
| 0.3042        | 0.55  | 2200 | 0.6484          |
| 0.2738        | 0.575 | 2300 | 0.6612          |
| 0.3121        | 0.6   | 2400 | 0.6684          |
| 0.2735        | 0.625 | 2500 | 0.6795          |
| 0.2595        | 0.65  | 2600 | 0.6802          |
| 0.2291        | 0.675 | 2700 | 0.6856          |
| 0.2239        | 0.7   | 2800 | 0.6964          |
| 0.2242        | 0.725 | 2900 | 0.7081          |
| 0.2357        | 0.75  | 3000 | 0.7200          |
| 0.2058        | 0.775 | 3100 | 0.7166          |
| 0.1881        | 0.8   | 3200 | 0.7303          |
| 0.1859        | 0.825 | 3300 | 0.7299          |
| 0.193         | 0.85  | 3400 | 0.7375          |
| 0.2061        | 0.875 | 3500 | 0.7392          |
| 0.1719        | 0.9   | 3600 | 0.7461          |
| 0.1908        | 0.925 | 3700 | 0.7464          |
| 0.1756        | 0.95  | 3800 | 0.7480          |
| 0.1863        | 0.975 | 3900 | 0.7489          |
| 0.1619        | 1.0   | 4000 | 0.7491          |


### Framework versions

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