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---
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 |