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Model: Cooolder/SCOPE-CoT-sft-v2
Source: Original Platform

README.md

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+---
+library_name: transformers
+license: other
+base_model: Qwen/Qwen3-4B-Instruct-2507
+tags:
+- llama-factory
+- full
+- generated_from_trainer
+model-index:
+- name: sft_cot
+  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. -->
+
+# sft_cot
+
+This model is a fine-tuned version of [Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507) on the scope_sft_cot dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3770
+
+## 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: 1e-05
+- train_batch_size: 1
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 8
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 1.0
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 0.5282        | 0.0763 | 500  | 0.5320          |
+| 0.5294        | 0.1526 | 1000 | 0.5253          |
+| 0.5116        | 0.2289 | 1500 | 0.5039          |
+| 0.5121        | 0.3052 | 2000 | 0.4850          |
+| 0.4778        | 0.3815 | 2500 | 0.4666          |
+| 0.4823        | 0.4578 | 3000 | 0.4533          |
+| 0.4292        | 0.5341 | 3500 | 0.4343          |
+| 0.4333        | 0.6104 | 4000 | 0.4167          |
+| 0.4153        | 0.6867 | 4500 | 0.4017          |
+| 0.3973        | 0.7630 | 5000 | 0.3908          |
+| 0.4168        | 0.8393 | 5500 | 0.3823          |
+| 0.3918        | 0.9156 | 6000 | 0.3777          |
+| 0.3942        | 0.9919 | 6500 | 0.3770          |
+
+
+### Framework versions
+
+- Transformers 4.57.1
+- Pytorch 2.7.1+cu126
+- Datasets 3.6.0
+- Tokenizers 0.22.1