Upload LoRA adapter - README.md

README.md

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+---
+library_name: peft
+license: apache-2.0
+base_model: Qwen/Qwen3-4B-Instruct-2507
+tags:
+- axolotl
+- base_model:adapter:Qwen/Qwen3-4B-Instruct-2507
+- lora
+- transformers
+datasets:
+- custom
+pipeline_tag: text-generation
+model-index:
+- name: checkpoints
+  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: `0.12.2`
+```yaml
+# 基础模型配置
+base_model: Qwen/Qwen3-4B-Instruct-2507
+load_in_4bit: true
+bnb_4bit_compute_dtype: bfloat16
+bnb_4bit_quant_type: nf4
+bnb_4bit_use_double_quant: true
+
+# LoRA配置
+adapter: lora
+lora_r: 64
+lora_alpha: 128
+lora_dropout: 0.05
+lora_target_modules:
+  - q_proj
+  - k_proj
+  - v_proj
+  - o_proj
+  - gate_proj
+  - up_proj
+  - down_proj
+lora_target_linear: true
+lora_fan_in_fan_out: false
+
+# 数据集
+chat_template: qwen3
+datasets:
+  - path: /workspace/tool_data_1012_89086.json
+    type: chat_template
+    roles_to_train: ["assistant"]
+    field_messages: messages
+    message_property_mappings:
+      role: role
+      content: content
+
+val_set_size: 0.05
+output_dir: checkpoints
+
+# 序列长度
+sequence_len: 8192
+pad_to_sequence_len: true
+sample_packing: false
+eval_sample_packing: false
+group_by_length: true
+
+# 训练参数
+num_epochs: 3
+micro_batch_size: 6
+gradient_accumulation_steps: 4
+eval_batch_size: 4
+
+# 优化器
+optimizer: adamw_bnb_8bit
+lr_scheduler: cosine_with_restarts
+cosine_restarts: 2
+learning_rate: 1e-4
+warmup_ratio: 0.05
+weight_decay: 0.01
+
+# 精度
+bf16: auto
+tf32: true
+gradient_checkpointing: true
+flash_attention: true
+
+# ========== 关键：保存策略 ==========
+save_strategy: steps
+eval_strategy: steps
+eval_steps: 500  # 每500步评估（约每1/6个epoch，根据数据量调整）
+save_steps: 500  # 与eval_steps一致
+
+save_total_limit: 1  # 只保留最优的1个
+load_best_model_at_end: true  # 训练结束加载最优
+metric_for_best_model: eval_loss  # 用验证集loss
+greater_is_better: false  # loss越小越好
+
+logging_steps: 30
+
+# DeepSpeed
+deepspeed: zero2.json
+
+# 其他
+ddp_timeout: 3600
+ddp_find_unused_parameters: false
+```
+
+</details><br>
+
+# checkpoints
+
+This model is a fine-tuned version of [Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507) on the /workspace/tool_data_1012_89086.json dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0672
+- Memory/max Mem Active(gib): 95.9
+- Memory/max Mem Allocated(gib): 95.9
+- Memory/device Mem Reserved(gib): 124.48
+
+## 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: 0.0001
+- train_batch_size: 6
+- eval_batch_size: 4
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 192
+- total_eval_batch_size: 32
+- optimizer: Use OptimizerNames.ADAMW_BNB 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_steps: 65
+- training_steps: 1310
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Mem Active(gib) | Mem Allocated(gib) | Mem Reserved(gib) |
+|:-------------:|:------:|:----:|:---------------:|:---------------:|:------------------:|:-----------------:|
+| No log        | 0      | 0    | 1.1993          | 50.61           | 50.61              | 51.0              |
+| 0.0695        | 1.1442 | 500  | 0.0686          | 95.9            | 95.9               | 124.48            |
+| 0.0681        | 2.2885 | 1000 | 0.0672          | 95.9            | 95.9               | 124.48            |
+
+
+### Framework versions
+
+- PEFT 0.17.0
+- Transformers 4.55.2
+- Pytorch 2.6.0+cu126
+- Datasets 4.0.0
+- Tokenizers 0.21.4