Dolphin 2.9.2 Qwen2 72B π¬
Curated and trained by Eric Hartford, Lucas Atkins, and Fernando Fernandes, and Cognitive Computations
Discord: https://discord.gg/cognitivecomputations
Our appreciation for the sponsors of Dolphin 2.9.2:
- Crusoe Cloud - provided excellent on-demand 8xH100 node
This model is based on Qwen2-72b, and is governed by tongyi-qianwen license
The base model has 128k context, and the full-weight fine-tuning was with 8k sequence length.
This model was trained FFT on parameters selected by Laser Scanner, using ChatML prompt template format.
example:
<|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 has a variety of instruction, conversational, and coding skills. It also has initial agentic abilities and supports function calling.
Dolphin is uncensored. We have filtered the dataset to remove alignment and bias. This makes the model more compliant. You are advised to implement your own alignment layer before exposing the model as a service. It will be highly compliant with any requests, even unethical ones. Please read my blog post about uncensored models. https://erichartford.com/uncensored-models You are responsible for any content you create using this model. Enjoy responsibly.
Dolphin is licensed according to Qwen's tongyi-qianwen license. We grant permission for any use, including commercial, that falls within accordance with said license. Dolphin was trained on data generated from GPT4, among other models.
Evals
See axolotl config
axolotl version: 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|>"
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 32.00 |
IFEval (0-Shot) | 40.38 |
BBH (3-Shot) | 47.70 |
MATH Lvl 5 (4-Shot) | 21.37 |
GPQA (0-shot) | 16.00 |
MuSR (0-shot) | 17.04 |
MMLU-PRO (5-shot) | 49.52 |
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Model tree for mav23/dolphin-2.9.2-qwen2-72b-GGUF
Base model
Qwen/Qwen2-72BDatasets used to train mav23/dolphin-2.9.2-qwen2-72b-GGUF
Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard40.380
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard47.700
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard21.370
- acc_norm on GPQA (0-shot)Open LLM Leaderboard16.000
- acc_norm on MuSR (0-shot)Open LLM Leaderboard17.040
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard49.520