mannix / dolphin-2.9.2-qwen2-72b

本模型基于Qwen2-72b，Dolphin-2.9.2具有各种指令、对话和编码技能。它还具备初始代理能力，并支持函数调用。Dolphin未经审查。

372次提取 更新于7周前

8周前

dce97e118f35 · 27GB

model
qwen2
·
72.7B
·
IQ2_XS
params
{"stop":["<|im_start|>","<|im_end|>"]}
template
{{ if .System }}<|im_start|>system {{ .System }}<|im_end|> {{ end }}{{ if .Prompt }}<|im_start|>user {{ .Prompt }}<|im_end|> {{ end }}<|im_start|>assistant {{ .Response }}<|im_end|>
license
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说明文档

Dolphin 2.9.2 Qwen2 72B 🐬

使用i-matrix calibration_datav3.txt进行量化，将safetensors转换为fp32

由Eric Hartford、Lucas Atkins、Fernando Fernandes和Cognitive Computations整理并训练

Discord
Discord: https://discord.gg/cognitivecomputations

感谢各位对Dolphin 2.9.2的赞助商
- Crusoe Cloud - 提供优秀的按需8xH100节点

本模型基于Qwen2-72b，受tongyi-qianwen许可规范

基础模型具有128k的上下文，通过8k序列长度进行完全加权的微调。

本模型使用Laser Scanner选择参数进行FFT训练，使用ChatML提示模板格式。

示例

<|im_start|>system
You are Dolphin, a helpful AI assistant.<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

Dolphin-2.9.2具有丰富的指令、对话和编码技能。它还具备初始代理能力，并支持函数调用。

Dolphin未经审查。我们对数据集进行了筛选，以去除对齐和偏差。这使得模型更符合规范。在将模型作为服务公开之前，建议您实现自己的对齐层。对于任何请求，即使是道德上有争议的请求，它都将非常规范。请阅读我关于未经审查的模型的博客文章。https://erichartford.com/uncensored-models 您对使用此模型生成的任何内容负责。负责任地享受。

海豚遵循Qwen的tongyi-qianwen许可证进行授权。我们允许任何符合该许可证的使用，包括商业用途。海豚在GPT4和其他模型生成数据上进行了训练。

评估

image/png

Built with Axolotl

参阅axolotl配置

axolotl版本：0.4.0

base_model: Qwen/Qwen2-72B
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer

trust_remote_code: true

# load_in_8bit: true
# load_in_4bit: false
# strict: false

datasets:
  - path: /workspace/datasets/dolphin-2.9.2/dolphin201-sharegpt2.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.2/dolphin-coder-codegen-sharegpt2.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.2/dolphin-coder-translate-sharegpt2.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.2/m-a-p_Code-Feedback-sharegpt-unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.2/m-a-p_CodeFeedback-Filtered-Instruction-sharegpt-unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.2/not_samantha_norefusals.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.2/openhermes200k_unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.2/Orca-Math-resort-unfiltered.jsonl
    type: sharegpt  
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.2/SystemChat_sharegpt.jsonl
    type: sharegpt  
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.2/toolbench_instruct_j1s1_3k_unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.2/toolbench_negative_unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.2/toolbench_react_10p_unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.2/toolbench_tflan_cot_30p_unfiltered.jsonl
    type: sharegpt 
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.2/agent_instruct_react_unfiltered.jsonl
    type: sharegpt
    conversation: chatml

unfrozen_parameters:
- ^lm_head.weight$
- ^model.embed_tokens.weight$
# mlp.down_proj layers
- model.layers.62.mlp.down_proj
- model.layers.63.mlp.down_proj
- model.layers.66.mlp.down_proj
- model.layers.65.mlp.down_proj
- model.layers.64.mlp.down_proj
- model.layers.67.mlp.down_proj
- model.layers.68.mlp.down_proj
- model.layers.60.mlp.down_proj
- model.layers.31.mlp.down_proj
- model.layers.69.mlp.down_proj
- model.layers.61.mlp.down_proj
- model.layers.59.mlp.down_proj
- model.layers.70.mlp.down_proj
- model.layers.30.mlp.down_proj
- model.layers.76.mlp.down_proj
- model.layers.72.mlp.down_proj
- model.layers.77.mlp.down_proj
- model.layers.71.mlp.down_proj
- model.layers.29.mlp.down_proj
- model.layers.58.mlp.down_proj
- model.layers.75.mlp.down_proj
- model.layers.32.mlp.down_proj
- model.layers.56.mlp.down_proj
- model.layers.28.mlp.down_proj
- model.layers.26.mlp.down_proj
- model.layers.33.mlp.down_proj
- model.layers.34.mlp.down_proj
- model.layers.57.mlp.down_proj
- model.layers.27.mlp.down_proj
- model.layers.25.mlp.down_proj
- model.layers.35.mlp.down_proj
- model.layers.73.mlp.down_proj
- model.layers.24.mlp.down_proj
- model.layers.78.mlp.down_proj
- model.layers.74.mlp.down_proj
- model.layers.54.mlp.down_proj
# mlp.gate_proj layers
- model.layers.78.mlp.gate_proj
- model.layers.77.mlp.gate_proj
- model.layers.76.mlp.gate_proj
- model.layers.79.mlp.gate_proj
- model.layers.75.mlp.gate_proj
- model.layers.74.mlp.gate_proj
- model.layers.73.mlp.gate_proj
- model.layers.70.mlp.gate_proj
- model.layers.72.mlp.gate_proj
- model.layers.71.mlp.gate_proj
- model.layers.69.mlp.gate_proj
- model.layers.54.mlp.gate_proj
- model.layers.68.mlp.gate_proj
- model.layers.57.mlp.gate_proj
- model.layers.63.mlp.gate_proj
- model.layers.49.mlp.gate_proj
- model.layers.55.mlp.gate_proj
- model.layers.53.mlp.gate_proj
- model.layers.44.mlp.gate_proj
- model.layers.46.mlp.gate_proj
- model.layers.67.mlp.gate_proj
- model.layers.58.mlp.gate_proj
- model.layers.56.mlp.gate_proj
- model.layers.45.mlp.gate_proj
- model.layers.50.mlp.gate_proj
- model.layers.62.mlp.gate_proj
- model.layers.64.mlp.gate_proj
- model.layers.48.mlp.gate_proj
- model.layers.66.mlp.gate_proj
- model.layers.52.mlp.gate_proj
- model.layers.40.mlp.gate_proj
- model.layers.47.mlp.gate_proj
- model.layers.43.mlp.gate_proj
- model.layers.65.mlp.gate_proj
- model.layers.61.mlp.gate_proj
- model.layers.59.mlp.gate_proj
# mlp.up_proj layers
- model.layers.69.mlp.up_proj
- model.layers.70.mlp.up_proj
- model.layers.71.mlp.up_proj
- model.layers.68.mlp.up_proj
- model.layers.67.mlp.up_proj
- model.layers.66.mlp.up_proj
- model.layers.46.mlp.up_proj
- model.layers.63.mlp.up_proj
- model.layers.72.mlp.up_proj
- model.layers.64.mlp.up_proj
- model.layers.62.mlp.up_proj
- model.layers.45.mlp.up_proj
- model.layers.65.mlp.up_proj
- model.layers.73.mlp.up_proj
- model.layers.47.mlp.up_proj
- model.layers.44.mlp.up_proj
- model.layers.49.mlp.up_proj
- model.layers.48.mlp.up_proj
- model.layers.53.mlp.up_proj
- model.layers.74.mlp.up_proj
- model.layers.75.mlp.up_proj
- model.layers.57.mlp.up_proj
- model.layers.76.mlp.up_proj
- model.layers.43.mlp.up_proj
- model.layers.42.mlp.up_proj
- model.layers.61.mlp.up_proj
- model.layers.40.mlp.up_proj
- model.layers.56.mlp.up_proj
- model.layers.60.mlp.up_proj
- model.layers.31.mlp.up_proj
- model.layers.54.mlp.up_proj
- model.layers.55.mlp.up_proj
- model.layers.32.mlp.up_proj
- model.layers.41.mlp.up_proj
- model.layers.33.mlp.up_proj
- model.layers.58.mlp.up_proj
# self_attn.k_proj layers
- model.layers.79.self_attn.k_proj
- model.layers.36.self_attn.k_proj
- model.layers.35.self_attn.k_proj
- model.layers.74.self_attn.k_proj
- model.layers.34.self_attn.k_proj
- model.layers.78.self_attn.k_proj
- model.layers.77.self_attn.k_proj
- model.layers.37.self_attn.k_proj
- model.layers.39.self_attn.k_proj
- model.layers.41.self_attn.k_proj
- model.layers.38.self_attn.k_proj
- model.layers.33.self_attn.k_proj
- model.layers.69.self_attn.k_proj
- model.layers.42.self_attn.k_proj
- model.layers.32.self_attn.k_proj
- model.layers.25.self_attn.k_proj
- model.layers.70.self_attn.k_proj
- model.layers.22.self_attn.k_proj
- model.layers.63.self_attn.k_proj
- model.layers.29.self_attn.k_proj
- model.layers.68.self_attn.k_proj
- model.layers.24.self_attn.k_proj
- model.layers.30.self_attn.k_proj
- model.layers.66.self_attn.k_proj
- model.layers.31.self_attn.k_proj
- model.layers.23.self_attn.k_proj
- model.layers.65.self_attn.k_proj
- model.layers.57.self_attn.k_proj
- model.layers.28.self_attn.k_proj
- model.layers.64.self_attn.k_proj
- model.layers.44.self_attn.k_proj
- model.layers.27.self_attn.k_proj
- model.layers.75.self_attn.k_proj
- model.layers.40.self_attn.k_proj
- model.layers.26.self_attn.k_proj
- model.layers.61.self_attn.k_proj
# self_attn.o_proj layers
- model.layers.14.self_attn.o_proj
- model.layers.39.self_attn.o_proj
- model.layers.19.self_attn.o_proj
- model.layers.16.self_attn.o_proj
- model.layers.17.self_attn.o_proj
- model.layers.15.self_attn.o_proj
- model.layers.69.self_attn.o_proj
- model.layers.12.self_attn.o_proj
- model.layers.42.self_attn.o_proj
- model.layers.23.self_attn.o_proj
- model.layers.22.self_attn.o_proj
- model.layers.29.self_attn.o_proj
- model.layers.13.self_attn.o_proj
- model.layers.46.self_attn.o_proj
- model.layers.52.self_attn.o_proj
- model.layers.26.self_attn.o_proj
- model.layers.38.self_attn.o_proj
- model.layers.41.self_attn.o_proj
- model.layers.18.self_attn.o_proj
- model.layers.49.self_attn.o_proj
- model.layers.11.self_attn.o_proj
- model.layers.28.self_attn.o_proj
- model.layers.25.self_attn.o_proj
- model.layers.47.self_attn.o_proj
- model.layers.53.self_attn.o_proj
- model.layers.27.self_attn.o_proj
- model.layers.37.self_attn.o_proj
- model.layers.20.self_attn.o_proj
- model.layers.43.self_attn.o_proj
- model.layers.44.self_attn.o_proj
- model.layers.45.self_attn.o_proj
- model.layers.30.self_attn.o_proj
- model.layers.24.self_attn.o_proj
- model.layers.21.self_attn.o_proj
- model.layers.10.self_attn.o_proj
- model.layers.3.self_attn.o_proj
# self_attn.q_proj layers
- model.layers.1.self_attn.q_proj
- model.layers.2.self_attn.q_proj
- model.layers.3.self_attn.q_proj
- model.layers.5.self_attn.q_proj
- model.layers.4.self_attn.q_proj
- model.layers.0.self_attn.q_proj
- model.layers.6.self_attn.q_proj
- model.layers.8.self_attn.q_proj
- model.layers.7.self_attn.q_proj
- model.layers.9.self_attn.q_proj
- model.layers.10.self_attn.q_proj
- model.layers.12.self_attn.q_proj
- model.layers.19.self_attn.q_proj
- model.layers.18.self_attn.q_proj
- model.layers.25.self_attn.q_proj
- model.layers.11.self_attn.q_proj
- model.layers.15.self_attn.q_proj
- model.layers.61.self_attn.q_proj
- model.layers.17.self_attn.q_proj
- model.layers.55.self_attn.q_proj
- model.layers.54.self_attn.q_proj
- model.layers.16.self_attn.q_proj
- model.layers.68.self_attn.q_proj
- model.layers.49.self_attn.q_proj
- model.layers.48.self_attn.q_proj
- model.layers.52.self_attn.q_proj
- model.layers.13.self_attn.q_proj
- model.layers.42.self_attn.q_proj
- model.layers.57.self_attn.q_proj
- model.layers.60.self_attn.q_proj
- model.layers.53.self_attn.q_proj
- model.layers.64.self_attn.q_proj
- model.layers.66.self_attn.q_proj
- model.layers.62.self_attn.q_proj
- model.layers.59.self_attn.q_proj
- model.layers.50.self_attn.q_proj
# self_attn.v_proj layers
- model.layers.15.self_attn.v_proj
- model.layers.16.self_attn.v_proj
- model.layers.23.self_attn.v_proj
- model.layers.24.self_attn.v_proj
- model.layers.25.self_attn.v_proj
- model.layers.26.self_attn.v_proj
- model.layers.27.self_attn.v_proj
- model.layers.28.self_attn.v_proj
- model.layers.29.self_attn.v_proj
- model.layers.30.self_attn.v_proj
- model.layers.31.self_attn.v_proj
- model.layers.32.self_attn.v_proj
- model.layers.33.self_attn.v_proj
- model.layers.34.self_attn.v_proj
- model.layers.35.self_attn.v_proj
- model.layers.36.self_attn.v_proj
- model.layers.37.self_attn.v_proj
- model.layers.38.self_attn.v_proj
- model.layers.39.self_attn.v_proj
- model.layers.41.self_attn.v_proj
- model.layers.42.self_attn.v_proj
- model.layers.48.self_attn.v_proj
- model.layers.53.self_attn.v_proj
- model.layers.57.self_attn.v_proj
- model.layers.58.self_attn.v_proj
- model.layers.59.self_attn.v_proj
- model.layers.61.self_attn.v_proj
- model.layers.63.self_attn.v_proj
- model.layers.64.self_attn.v_proj
- model.layers.65.self_attn.v_proj
- model.layers.66.self_attn.v_proj
- model.layers.69.self_attn.v_proj
- model.layers.74.self_attn.v_proj
- model.layers.75.self_attn.v_proj
- model.layers.76.self_attn.v_proj
- model.layers.72.self_attn.v_proj

  
chat_template: chatml
dataset_prepared_path: qwen2-72b-data
val_set_size: 0.01
output_dir: qwen2-72b

sequence_len: 8192  # supports up to 8192
sample_packing: true
pad_to_sequence_len: true

# adapter: lora
# lora_model_dir:
# lora_r: 32
# lora_alpha: 16
# lora_dropout: 0.05
# lora_target_linear: true
# lora_fan_in_fan_out:

wandb_project: qwen2-72b
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:

gradient_accumulation_steps: 8
micro_batch_size: 1
num_epochs: 3
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 1e-5

train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_steps: 10
evals_per_epoch: 2
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 4
save_total_limit: 2
debug:
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16_cpuoffload_params.json
weight_decay: 0.05
fsdp:
fsdp_config:
special_tokens:
  pad_token: "<|endoftext|>"
  eos_token: "<|im_end|>"