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Ministral-8B-Instruct-2410-PsyCourse-fold3

PEFT
Safetensors
llama-factory
lora
Generated from Trainer
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README.md ADDED
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+ ---
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+ library_name: peft
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+ license: other
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+ base_model: mistralai/Ministral-8B-Instruct-2410
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+ tags:
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+ - llama-factory
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+ - generated_from_trainer
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+ model-index:
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+ - name: Ministral-8B-Instruct-2410-PsyCourse-fold3
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+ results: []
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+ ---
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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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+
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+ # Ministral-8B-Instruct-2410-PsyCourse-fold3
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+
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+ This model is a fine-tuned version of [mistralai/Ministral-8B-Instruct-2410](https://huggingface.co/mistralai/Ministral-8B-Instruct-2410) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0487
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 1
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+ - eval_batch_size: 1
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+ - seed: 42
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+ - gradient_accumulation_steps: 16
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+ - total_train_batch_size: 16
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+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 5.0
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:----:|:---------------:|
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+ | 0.2581 | 0.0770 | 50 | 0.2414 |
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+ | 0.0852 | 0.1539 | 100 | 0.0696 |
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+ | 0.0612 | 0.2309 | 150 | 0.0584 |
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+ | 0.0579 | 0.3078 | 200 | 0.0537 |
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+ | 0.0436 | 0.3848 | 250 | 0.0433 |
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+ | 0.0395 | 0.4617 | 300 | 0.0470 |
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+ | 0.0436 | 0.5387 | 350 | 0.0454 |
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+ | 0.0487 | 0.6156 | 400 | 0.0436 |
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+ | 0.0302 | 0.6926 | 450 | 0.0377 |
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+ | 0.0301 | 0.7695 | 500 | 0.0377 |
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+ | 0.0422 | 0.8465 | 550 | 0.0353 |
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+ | 0.0352 | 0.9234 | 600 | 0.0341 |
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+ | 0.0327 | 1.0004 | 650 | 0.0346 |
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+ | 0.0328 | 1.0773 | 700 | 0.0361 |
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+ | 0.0278 | 1.1543 | 750 | 0.0347 |
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+ | 0.0277 | 1.2312 | 800 | 0.0336 |
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+ | 0.0278 | 1.3082 | 850 | 0.0347 |
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+ | 0.0208 | 1.3851 | 900 | 0.0341 |
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+ | 0.037 | 1.4621 | 950 | 0.0345 |
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+ | 0.0335 | 1.5391 | 1000 | 0.0357 |
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+ | 0.0305 | 1.6160 | 1050 | 0.0322 |
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+ | 0.0337 | 1.6930 | 1100 | 0.0377 |
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+ | 0.0221 | 1.7699 | 1150 | 0.0325 |
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+ | 0.0192 | 1.8469 | 1200 | 0.0378 |
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+ | 0.0282 | 1.9238 | 1250 | 0.0325 |
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+ | 0.0216 | 2.0008 | 1300 | 0.0309 |
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+ | 0.0172 | 2.0777 | 1350 | 0.0312 |
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+ | 0.0238 | 2.1547 | 1400 | 0.0342 |
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+ | 0.0118 | 2.2316 | 1450 | 0.0379 |
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+ | 0.02 | 2.3086 | 1500 | 0.0349 |
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+ | 0.0162 | 2.3855 | 1550 | 0.0389 |
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+ | 0.0138 | 2.4625 | 1600 | 0.0367 |
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+ | 0.0193 | 2.5394 | 1650 | 0.0348 |
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+ | 0.0208 | 2.6164 | 1700 | 0.0356 |
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+ | 0.0228 | 2.6933 | 1750 | 0.0326 |
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+ | 0.0195 | 2.7703 | 1800 | 0.0323 |
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+ | 0.0219 | 2.8472 | 1850 | 0.0317 |
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+ | 0.0169 | 2.9242 | 1900 | 0.0329 |
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+ | 0.0235 | 3.0012 | 1950 | 0.0340 |
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+ | 0.0092 | 3.0781 | 2000 | 0.0377 |
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+ | 0.0107 | 3.1551 | 2050 | 0.0413 |
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+ | 0.0093 | 3.2320 | 2100 | 0.0398 |
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+ | 0.0076 | 3.3090 | 2150 | 0.0406 |
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+ | 0.0115 | 3.3859 | 2200 | 0.0380 |
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+ | 0.0065 | 3.4629 | 2250 | 0.0371 |
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+ | 0.0115 | 3.5398 | 2300 | 0.0394 |
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+ | 0.006 | 3.6168 | 2350 | 0.0399 |
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+ | 0.0119 | 3.6937 | 2400 | 0.0366 |
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+ | 0.0068 | 3.7707 | 2450 | 0.0387 |
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+ | 0.0079 | 3.8476 | 2500 | 0.0394 |
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+ | 0.0092 | 3.9246 | 2550 | 0.0405 |
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+ | 0.0088 | 4.0015 | 2600 | 0.0393 |
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+ | 0.0017 | 4.0785 | 2650 | 0.0415 |
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+ | 0.0076 | 4.1554 | 2700 | 0.0446 |
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+ | 0.0017 | 4.2324 | 2750 | 0.0453 |
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+ | 0.0027 | 4.3093 | 2800 | 0.0469 |
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+ | 0.003 | 4.3863 | 2850 | 0.0485 |
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+ | 0.0047 | 4.4633 | 2900 | 0.0493 |
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+ | 0.0021 | 4.5402 | 2950 | 0.0484 |
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+ | 0.0031 | 4.6172 | 3000 | 0.0485 |
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+ | 0.0036 | 4.6941 | 3050 | 0.0488 |
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+ | 0.0028 | 4.7711 | 3100 | 0.0488 |
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+ | 0.0031 | 4.8480 | 3150 | 0.0487 |
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+ | 0.0035 | 4.9250 | 3200 | 0.0487 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.12.0
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+ - Transformers 4.46.1
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.3
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