---
library_name: peft
license: other
base_model: deepseek-ai/deepseek-llm-7b-base
tags:
- generated_from_trainer
model-index:
- name: deepseek-Instruct-8B
  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-Instruct-8B

This model is a fine-tuned version of [deepseek-ai/deepseek-llm-7b-base](https://huggingface.co/deepseek-ai/deepseek-llm-7b-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2329

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- 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: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.9256        | 0.1144 | 50   | 1.8577          |
| 1.4949        | 0.2288 | 100  | 0.9622          |
| 0.5315        | 0.3432 | 150  | 0.3328          |
| 0.3079        | 0.4577 | 200  | 0.3011          |
| 0.2974        | 0.5721 | 250  | 0.2960          |
| 0.2921        | 0.6865 | 300  | 0.2903          |
| 0.2869        | 0.8009 | 350  | 0.2832          |
| 0.2757        | 0.9153 | 400  | 0.2731          |
| 0.2676        | 1.0297 | 450  | 0.2644          |
| 0.2594        | 1.1442 | 500  | 0.2590          |
| 0.2546        | 1.2586 | 550  | 0.2535          |
| 0.2497        | 1.3730 | 600  | 0.2505          |
| 0.2477        | 1.4874 | 650  | 0.2489          |
| 0.2462        | 1.6018 | 700  | 0.2463          |
| 0.2438        | 1.7162 | 750  | 0.2452          |
| 0.2439        | 1.8307 | 800  | 0.2436          |
| 0.2434        | 1.9451 | 850  | 0.2426          |
| 0.2414        | 2.0595 | 900  | 0.2415          |
| 0.2408        | 2.1739 | 950  | 0.2406          |
| 0.2374        | 2.2883 | 1000 | 0.2396          |
| 0.2388        | 2.4027 | 1050 | 0.2385          |
| 0.2357        | 2.5172 | 1100 | 0.2378          |
| 0.2358        | 2.6316 | 1150 | 0.2377          |
| 0.236         | 2.7460 | 1200 | 0.2371          |
| 0.2352        | 2.8604 | 1250 | 0.2361          |
| 0.2342        | 2.9748 | 1300 | 0.2357          |
| 0.2337        | 3.0892 | 1350 | 0.2352          |
| 0.2337        | 3.2037 | 1400 | 0.2346          |
| 0.2335        | 3.3181 | 1450 | 0.2343          |
| 0.2327        | 3.4325 | 1500 | 0.2337          |
| 0.2314        | 3.5469 | 1550 | 0.2337          |
| 0.2322        | 3.6613 | 1600 | 0.2334          |
| 0.2318        | 3.7757 | 1650 | 0.2330          |
| 0.2292        | 3.8902 | 1700 | 0.2329          |


### Framework versions

- PEFT 0.14.0
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1