upload model weights

.gitattributes

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README.md

@@ -1,6 +1,70 @@
 ---
-license: apache-2.0
+library_name: transformers
+license: other
+base_model: /data/HUHE/benchmark_weight/sijuzheng/models/qwen3_8b/Qwen/Qwen3-8B
+tags:
+- llama-factory
+- full
+- generated_from_trainer
+model-index:
+- name: multi_turn_phy_dataset_qwen3_8b_80p
+  results: []
 ---
-## Paper
-This model is described in the paper:
-[arXiv:2505.15715](https://arxiv.org/abs/2505.15715)
+
+<!-- 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. -->
+
+# multi_turn_phy_dataset_qwen3_8b_80p
+
+This model is a fine-tuned version of [/data/HUHE/benchmark_weight/sijuzheng/models/qwen3_8b/Qwen/Qwen3-8B](https://huggingface.co//data/HUHE/benchmark_weight/sijuzheng/models/qwen3_8b/Qwen/Qwen3-8B) on the multi_xinli_r1_sharegpt_80p dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7997
+
+## 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: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- total_eval_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: 3.0
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 0.8472        | 0.5889 | 500  | 0.8460          |
+| 0.6536        | 1.1779 | 1000 | 0.8132          |
+| 0.6318        | 1.7668 | 1500 | 0.7878          |
+| 0.5161        | 2.3557 | 2000 | 0.8036          |
+| 0.4941        | 2.9446 | 2500 | 0.7997          |
+
+
+### Framework versions
+
+- Transformers 4.51.0
+- Pytorch 2.3.0+cu121
+- Datasets 3.4.1
+- Tokenizers 0.21.0

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