初始化项目，由ModelHub XC社区提供模型

Model: laion/alfworld-swesmith-r2egym-swegym-131k-lc
Source: Original Platform

README.md

@@ -0,0 +1,61 @@
+---
+library_name: transformers
+license: other
+base_model: Qwen/Qwen3-8B
+tags:
+- llama-factory
+- full
+- generated_from_trainer
+model-index:
+- name: sft__glm46-neulab-agenttuning-alfworld-sandboxes-maxeps-131k-glm46-swesmith-maxeps-131k-GLM-4-7
+  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__glm46-neulab-agenttuning-alfworld-sandboxes-maxeps-131k-glm46-swesmith-maxeps-131k-GLM-4-7
+
+This model is a fine-tuned version of [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) on the /e/data1/datasets/playground/ot/hf_hub/datasets--penfever--glm46-neulab-agenttuning-alfworld-sandboxes-maxeps-131k/snapshots/fdb0d0afe08aa3c31c7605b40c18d5e48fdc206c_thinking_preprocessed, the /e/data1/datasets/playground/ot/hf_hub/datasets--penfever--glm46-swesmith-maxeps-131k/snapshots/4d4c2d4a9d21f73870ed31c7bc6028035b3b6ca7_thinking_preprocessed, the /e/data1/datasets/playground/ot/hf_hub/datasets--DCAgent2--GLM-4.7-r2egym_sandboxes-maxeps-131k/snapshots/167ff86e8203fa2412574480bf52623cb62320e8_thinking_preprocessed and the /e/data1/datasets/playground/ot/hf_hub/datasets--DCAgent2--glm46-swegym-tasks-maxeps-131k/snapshots/bc7a253d567261d84db295a138b8af86eac6ae4c_thinking_preprocessed datasets.
+
+## 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: 4e-05
+- train_batch_size: 1
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 48
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 96
+- total_eval_batch_size: 384
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.98) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 7.0
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.57.6
+- Pytorch 2.9.1+cu130
+- Datasets 4.7.0
+- Tokenizers 0.22.2