---
base_model: deepseek-ai/deepseek-coder-6.7b-base
library_name: peft
license: other
tags:
- unsloth
- generated_from_trainer
model-index:
- name: deepseek-coder-6.7b-base-APR-FIM-finetuning
  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. -->

# deepseek-coder-6.7b-base-APR-FIM-finetuning

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: 0.5779

## 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: 16
- eval_batch_size: 16
- seed: 11
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 2000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6471        | 0.05  | 100  | 0.6437          |
| 0.6132        | 0.1   | 200  | 0.6208          |
| 0.6719        | 0.15  | 300  | 0.6141          |
| 0.6325        | 0.2   | 400  | 0.6089          |
| 0.6124        | 0.25  | 500  | 0.6054          |
| 0.5842        | 0.3   | 600  | 0.6023          |
| 0.5537        | 0.35  | 700  | 0.5982          |
| 0.5966        | 0.4   | 800  | 0.5951          |
| 0.5757        | 0.45  | 900  | 0.5921          |
| 0.5856        | 0.5   | 1000 | 0.5879          |
| 0.6049        | 0.55  | 1100 | 0.5864          |
| 0.5611        | 0.6   | 1200 | 0.5841          |
| 0.5753        | 0.65  | 1300 | 0.5821          |
| 0.541         | 0.7   | 1400 | 0.5810          |
| 0.5838        | 0.75  | 1500 | 0.5795          |
| 0.5326        | 0.8   | 1600 | 0.5789          |
| 0.5292        | 0.85  | 1700 | 0.5784          |
| 0.5548        | 0.9   | 1800 | 0.5780          |
| 0.552         | 0.95  | 1900 | 0.5779          |
| 0.9524        | 1.0   | 2000 | 0.5779          |


### Framework versions

- PEFT 0.13.0
- Transformers 4.44.2
- Pytorch 2.1.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1