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--- a/README.md
+++ b/README.md
@@ -1,47 +1,288 @@
 ---
-license: Apache License 2.0
-
-#model-type:
-##如 gpt、phi、llama、chatglm、baichuan 等
-#- gpt
-
-#domain:
-##如 nlp、cv、audio、multi-modal
-#- nlp
-
-#language:
-##语言代码列表 https://help.aliyun.com/document_detail/215387.html?spm=a2c4g.11186623.0.0.9f8d7467kni6Aa
-#- cn 
-
-#metrics:
-##如 CIDEr、Blue、ROUGE 等
-#- CIDEr
-
-#tags:
-##各种自定义，包括 pretrained、fine-tuned、instruction-tuned、RL-tuned 等训练方法和其他
-#- pretrained
-
-#tools:
-##如 vllm、fastchat、llamacpp、AdaSeq 等
-#- vllm
+license: llama3.1
+base_model: Crystalcareai/Meta-llama-3.1-8b-instruct
+tags:
+- generated_from_trainer
+model-index:
+- name: outputs/out-myalee
+  results: []
 ---
-### 当前模型的贡献者未提供更加详细的模型介绍。模型文件和权重，可浏览“模型文件”页面获取。
-#### 您可以通过如下git clone命令，或者ModelScope SDK来下载模型

-SDK下载
-```bash
-#安装ModelScope
-pip install modelscope
-```
-```python
-#SDK模型下载
-from modelscope import snapshot_download
-model_dir = snapshot_download('arcee-ai/myalee-v3-L31-8B')
-```
-Git下载
-```
-#Git模型下载
-git clone https://www.modelscope.cn/arcee-ai/myalee-v3-L31-8B.git
+<!-- 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: `0.4.1`
+```yaml
+base_model: Crystalcareai/Meta-llama-3.1-8b-instruct
+model_type: AutoTokenizer
+tokenizer_type: AutoTokenizer
+
+load_in_8bit: false
+load_in_4bit: false
+strict: false
+
+datasets:
+  - path: /workspace/data/myalee
+    type: alpaca
+  - path: mlabonne/FineTome-100k
+    type: sharegpt
+
+chat_template: llama3
+dataset_prepared_path: last_run_prepared
+# val_set_size: 0.05
+output_dir: ./outputs/out-myalee
+
+sequence_len: 8192
+sample_packing: true
+pad_to_sequence_len: true
+
+wandb_project:
+wandb_entity:
+wandb_watch:
+wandb_name:
+wandb_log_model:
+
+unfrozen_parameters:
+- ^lm_head.weight$
+- ^model.embed_tokens.weight$
+# input_layernorm layers
+- model.layers.0.input_layernorm
+- model.layers.1.input_layernorm
+- model.layers.2.input_layernorm
+- model.layers.3.input_layernorm
+- model.layers.4.input_layernorm
+- model.layers.5.input_layernorm
+- model.layers.6.input_layernorm
+- model.layers.7.input_layernorm
+- model.layers.8.input_layernorm
+- model.layers.9.input_layernorm
+- model.layers.10.input_layernorm
+- model.layers.11.input_layernorm
+- model.layers.12.input_layernorm
+- model.layers.13.input_layernorm
+- model.layers.14.input_layernorm
+- model.layers.15.input_layernorm
+# lm_head layers
+# mlp.down_proj layers
+- model.layers.1.mlp.down_proj
+- model.layers.0.mlp.down_proj
+- model.layers.30.mlp.down_proj
+- model.layers.2.mlp.down_proj
+- model.layers.21.mlp.down_proj
+- model.layers.22.mlp.down_proj
+- model.layers.29.mlp.down_proj
+- model.layers.5.mlp.down_proj
+- model.layers.4.mlp.down_proj
+- model.layers.20.mlp.down_proj
+- model.layers.23.mlp.down_proj
+- model.layers.19.mlp.down_proj
+- model.layers.3.mlp.down_proj
+- model.layers.17.mlp.down_proj
+- model.layers.6.mlp.down_proj
+- model.layers.31.mlp.down_proj
+# mlp.gate_proj layers
+- model.layers.1.mlp.gate_proj
+- model.layers.2.mlp.gate_proj
+- model.layers.3.mlp.gate_proj
+- model.layers.4.mlp.gate_proj
+- model.layers.0.mlp.gate_proj
+- model.layers.25.mlp.gate_proj
+- model.layers.26.mlp.gate_proj
+- model.layers.5.mlp.gate_proj
+- model.layers.24.mlp.gate_proj
+- model.layers.28.mlp.gate_proj
+- model.layers.23.mlp.gate_proj
+- model.layers.27.mlp.gate_proj
+- model.layers.21.mlp.gate_proj
+- model.layers.22.mlp.gate_proj
+- model.layers.29.mlp.gate_proj
+- model.layers.20.mlp.gate_proj
+# mlp.up_proj layers
+- model.layers.4.mlp.up_proj
+- model.layers.3.mlp.up_proj
+- model.layers.0.mlp.up_proj
+- model.layers.5.mlp.up_proj
+- model.layers.7.mlp.up_proj
+- model.layers.6.mlp.up_proj
+- model.layers.2.mlp.up_proj
+- model.layers.1.mlp.up_proj
+- model.layers.8.mlp.up_proj
+- model.layers.12.mlp.up_proj
+- model.layers.14.mlp.up_proj
+- model.layers.9.mlp.up_proj
+- model.layers.15.mlp.up_proj
+- model.layers.17.mlp.up_proj
+- model.layers.13.mlp.up_proj
+- model.layers.19.mlp.up_proj
+# model.embed_tokens layers
+# model.norm layers
+# post_attention_layernorm layers
+- model.layers.0.post_attention_layernorm
+- model.layers.1.post_attention_layernorm
+- model.layers.2.post_attention_layernorm
+- model.layers.3.post_attention_layernorm
+- model.layers.4.post_attention_layernorm
+- model.layers.5.post_attention_layernorm
+- model.layers.6.post_attention_layernorm
+- model.layers.7.post_attention_layernorm
+- model.layers.8.post_attention_layernorm
+- model.layers.9.post_attention_layernorm
+- model.layers.10.post_attention_layernorm
+- model.layers.11.post_attention_layernorm
+- model.layers.12.post_attention_layernorm
+- model.layers.13.post_attention_layernorm
+- model.layers.14.post_attention_layernorm
+- model.layers.15.post_attention_layernorm
+# self_attn.k_proj layers
+- model.layers.29.self_attn.k_proj
+- model.layers.25.self_attn.k_proj
+- model.layers.23.self_attn.k_proj
+- model.layers.28.self_attn.k_proj
+- model.layers.21.self_attn.k_proj
+- model.layers.19.self_attn.k_proj
+- model.layers.22.self_attn.k_proj
+- model.layers.20.self_attn.k_proj
+- model.layers.24.self_attn.k_proj
+- model.layers.31.self_attn.k_proj
+- model.layers.27.self_attn.k_proj
+- model.layers.26.self_attn.k_proj
+- model.layers.17.self_attn.k_proj
+- model.layers.11.self_attn.k_proj
+- model.layers.18.self_attn.k_proj
+- model.layers.14.self_attn.k_proj
+# self_attn.o_proj layers
+- model.layers.14.self_attn.o_proj
+- model.layers.7.self_attn.o_proj
+- model.layers.5.self_attn.o_proj
+- model.layers.11.self_attn.o_proj
+- model.layers.6.self_attn.o_proj
+- model.layers.24.self_attn.o_proj
+- model.layers.9.self_attn.o_proj
+- model.layers.13.self_attn.o_proj
+- model.layers.10.self_attn.o_proj
+- model.layers.12.self_attn.o_proj
+- model.layers.8.self_attn.o_proj
+- model.layers.25.self_attn.o_proj
+- model.layers.21.self_attn.o_proj
+- model.layers.23.self_attn.o_proj
+- model.layers.15.self_attn.o_proj
+- model.layers.16.self_attn.o_proj
+# self_attn.q_proj layers
+- model.layers.8.self_attn.q_proj
+- model.layers.13.self_attn.q_proj
+- model.layers.9.self_attn.q_proj
+- model.layers.14.self_attn.q_proj
+- model.layers.10.self_attn.q_proj
+- model.layers.11.self_attn.q_proj
+- model.layers.0.self_attn.q_proj
+- model.layers.15.self_attn.q_proj
+- model.layers.1.self_attn.q_proj
+- model.layers.6.self_attn.q_proj
+- model.layers.5.self_attn.q_proj
+- model.layers.7.self_attn.q_proj
+- model.layers.12.self_attn.q_proj
+- model.layers.16.self_attn.q_proj
+- model.layers.17.self_attn.q_proj
+- model.layers.26.self_attn.q_proj
+# self_attn.v_proj layers
+- model.layers.26.self_attn.v_proj
+- model.layers.17.self_attn.v_proj
+- model.layers.3.self_attn.v_proj
+- model.layers.28.self_attn.v_proj
+- model.layers.29.self_attn.v_proj
+- model.layers.21.self_attn.v_proj
+- model.layers.15.self_attn.v_proj
+- model.layers.16.self_attn.v_proj
+- model.layers.20.self_attn.v_proj
+- model.layers.25.self_attn.v_proj
+- model.layers.6.self_attn.v_proj
+- model.layers.23.self_attn.v_proj
+- model.layers.4.self_attn.v_proj
+- model.layers.1.self_attn.v_proj
+- model.layers.22.self_attn.v_proj
+- model.layers.14.self_attn.v_proj
+
+
+gradient_accumulation_steps: 8
+micro_batch_size: 1
+num_epochs: 4
+optimizer: adamw_torch_fused
+lr_scheduler: cosine
+learning_rate: 2e-5
+
+train_on_inputs: false
+group_by_length: false
+bf16: auto
+fp16:
+tf32: false
+
+gradient_checkpointing: true
+gradient_checkpointing_kwargs:
+  use_reentrant: false
+early_stopping_patience:
+resume_from_checkpoint:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+
+warmup_steps: 25
+# evals_per_epoch: 2
+eval_table_size:
+saves_per_epoch: 1
+debug:
+deepspeed:
+weight_decay: 0.0
+fsdp:
+fsdp_config:
+special_tokens:
+  pad_token: <|end_of_text|>
+
 ```

-<p style="color: lightgrey;">如果您是本模型的贡献者，我们邀请您根据<a href="https://modelscope.cn/docs/ModelScope%E6%A8%A1%E5%9E%8B%E6%8E%A5%E5%85%A5%E6%B5%81%E7%A8%8B%E6%A6%82%E8%A7%88" style="color: lightgrey; text-decoration: underline;">模型贡献文档</a>，及时完善模型卡片内容。</p>
+</details><br>
+
+# outputs/out-myalee
+
+This model is a fine-tuned version of [Crystalcareai/Meta-llama-3.1-8b-instruct](https://huggingface.co/Crystalcareai/Meta-llama-3.1-8b-instruct) on the None 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: 2e-05
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 25
+- num_epochs: 4
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.43.1
+- Pytorch 2.3.1+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1