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--- |
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library_name: peft |
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license: other |
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base_model: deepseek-ai/deepseek-llm-7b-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: deepseek-Instruct-8B |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# deepseek-Instruct-8B |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2329 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 4 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.9256 | 0.1144 | 50 | 1.8577 | |
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| 1.4949 | 0.2288 | 100 | 0.9622 | |
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| 0.5315 | 0.3432 | 150 | 0.3328 | |
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| 0.3079 | 0.4577 | 200 | 0.3011 | |
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| 0.2974 | 0.5721 | 250 | 0.2960 | |
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| 0.2921 | 0.6865 | 300 | 0.2903 | |
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| 0.2869 | 0.8009 | 350 | 0.2832 | |
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| 0.2757 | 0.9153 | 400 | 0.2731 | |
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| 0.2676 | 1.0297 | 450 | 0.2644 | |
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| 0.2594 | 1.1442 | 500 | 0.2590 | |
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| 0.2546 | 1.2586 | 550 | 0.2535 | |
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| 0.2497 | 1.3730 | 600 | 0.2505 | |
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| 0.2477 | 1.4874 | 650 | 0.2489 | |
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| 0.2462 | 1.6018 | 700 | 0.2463 | |
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| 0.2438 | 1.7162 | 750 | 0.2452 | |
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| 0.2439 | 1.8307 | 800 | 0.2436 | |
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| 0.2434 | 1.9451 | 850 | 0.2426 | |
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| 0.2414 | 2.0595 | 900 | 0.2415 | |
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| 0.2408 | 2.1739 | 950 | 0.2406 | |
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| 0.2374 | 2.2883 | 1000 | 0.2396 | |
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| 0.2388 | 2.4027 | 1050 | 0.2385 | |
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| 0.2357 | 2.5172 | 1100 | 0.2378 | |
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| 0.2358 | 2.6316 | 1150 | 0.2377 | |
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| 0.236 | 2.7460 | 1200 | 0.2371 | |
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| 0.2352 | 2.8604 | 1250 | 0.2361 | |
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| 0.2342 | 2.9748 | 1300 | 0.2357 | |
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| 0.2337 | 3.0892 | 1350 | 0.2352 | |
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| 0.2337 | 3.2037 | 1400 | 0.2346 | |
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| 0.2335 | 3.3181 | 1450 | 0.2343 | |
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| 0.2327 | 3.4325 | 1500 | 0.2337 | |
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| 0.2314 | 3.5469 | 1550 | 0.2337 | |
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| 0.2322 | 3.6613 | 1600 | 0.2334 | |
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| 0.2318 | 3.7757 | 1650 | 0.2330 | |
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| 0.2292 | 3.8902 | 1700 | 0.2329 | |
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### Framework versions |
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- PEFT 0.14.0 |
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- Transformers 4.50.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.5.0 |
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- Tokenizers 0.21.1 |
