初始化项目，由ModelHub XC社区提供模型

Model: allura-forge/allura-forge-PluraLM-7B-SFT
Source: Original Platform

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: Qwen/Qwen2.5-7B-Instruct
+tags:
+- generated_from_trainer
+datasets:
+- pluralm-qwen25.parquet
+model-index:
+- name: model-output
+  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. -->
+
+[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.13.0.dev0`
+```yaml
+base_model: Qwen/Qwen2.5-7B-Instruct
+trust_remote_code: true
+
+strict: false
+
+# < -- Saving -- >
+output_dir: ./model-output
+saves_per_epoch: 4
+
+
+# < -- Vram Savings -- >
+#gradient_checkpointing: true
+flash_attention: true
+
+fsdp:
+  - auto_wrap
+  - full_shard
+fsdp_config:
+  fsdp_version: 2
+  fsdp_offload_params: false
+  fsdp_cpu_ram_efficient_loading: true
+  fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
+  fsdp_transformer_layer_cls_to_wrap: Qwen2DecoderLayer
+  fsdp_state_dict_type: SHARDED_STATE_DICT
+  fsdp_sharding_strategy: FULL_SHARD
+  fsdp_reshard_after_forward: true
+  fsdp_activation_checkpointing: true # will disable if doesnt work
+
+# === Plugins ===
+plugins:
+  - axolotl.integrations.liger.LigerPlugin
+  - axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
+liger_rope: true
+liger_rms_norm: true
+liger_glu_activation: true
+cut_cross_entropy: true
+
+# < -- Evals -- >
+#evals_per_epoch
+#eval_steps: 100
+val_set_size: 0.0
+
+# < -- Hparams -- >
+warmup_steps: 5
+sequence_len: 8192
+sample_packing: true
+eval_sample_packing: false
+pad_to_sequence_len: true
+
+weight_decay: 0.0
+gradient_accumulation_steps: 1
+micro_batch_size: 2
+num_epochs: 2
+max_grad_norm: 0.01
+optimizer: adamw_torch_8bit
+lr_scheduler: cosine
+learning_rate: 1e-5
+
+## data 
+datasets:
+  - path: pluralm-qwen25.parquet
+    ds_type: parquet
+    type: 
+
+shuffle_merged_datasets: true
+dataset_prepared_path: last_run_prepared
+remove_unused_columns: false
+
+# < -- wandb -- >
+wandb_project: PlurLM 7b
+wandb_entity:
+wandb_watch:
+wandb_name: introject
+wandb_log_model:
+
+# < -- Misc -- >
+train_on_inputs: false
+group_by_length: false
+bf16: auto
+fp16:
+tf32: false
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention:
+
+
+```
+
+</details><br>
+
+# model-output
+
+This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the pluralm-qwen25.parquet dataset.
+
+## 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: 2
+- eval_batch_size: 2
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- total_train_batch_size: 16
+- total_eval_batch_size: 16
+- optimizer: Use OptimizerNames.ADAMW_TORCH_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 5
+- training_steps: 48
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.55.4
+- Pytorch 2.8.0+cu128
+- Datasets 4.0.0
+- Tokenizers 0.21.4