Model save

README.md

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+---
+library_name: transformers
+base_model: PowerInfer/SmallThinker-3B-Preview
+tags:
+- generated_from_trainer
+model-index:
+- name: smartmind-cyberone-20250402
+  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. -->
+
+# smartmind-cyberone-20250402
+
+This model is a fine-tuned version of [PowerInfer/SmallThinker-3B-Preview](https://huggingface.co/PowerInfer/SmallThinker-3B-Preview) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0308
+
+## 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: 2e-05
+- train_batch_size: 64
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- gradient_accumulation_steps: 64
+- total_train_batch_size: 4096
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine_with_restarts
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 0.3817        | 0.3527 | 30   | 0.2134          |
+| 0.1292        | 0.7054 | 60   | 0.0959          |
+| 0.0931        | 1.0470 | 90   | 0.3264          |
+| 0.125         | 1.3997 | 120  | 0.0485          |
+| 0.057         | 1.7524 | 150  | 0.0569          |
+| 0.0503        | 2.0940 | 180  | 0.0444          |
+| 0.0444        | 2.4467 | 210  | 0.0426          |
+| 0.0405        | 2.7994 | 240  | 0.0346          |
+| 0.0472        | 3.1411 | 270  | 0.0614          |
+| 0.045         | 3.4938 | 300  | 0.0406          |
+| 0.0405        | 3.8464 | 330  | 0.0328          |
+| 0.0345        | 4.1881 | 360  | 0.0300          |
+| 0.0333        | 4.5408 | 390  | 0.0363          |
+| 0.0325        | 4.8935 | 420  | 0.0308          |
+
+
+### Framework versions
+
+- Transformers 4.50.3
+- Pytorch 2.5.1+cu124
+- Datasets 3.5.0
+- Tokenizers 0.21.1

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