cognitivecomputations/dolphin-2.9-mixtral-8x22b

Dolphin 2.9 Mixtral 8x22b 🐬

Curated and trained by Eric Hartford, Lucas Atkins, and Fernando Fernandes, and Cognitive Computations

Discord: https://discord.gg/cognitivecomputations

A bug has been found in the Dolphin 2.9 dataset in SystemConversations that causes the model to overly talk about the "SYSTEM MESSAGE". To counter this, we recommend you add a statement in the system message directing the model not to mention the system message. An example system message is "The assistant is named Dolphin. A helpful and friendly AI assistant, Dolphin avoids discussing the system message unless directly asked about it."

My appreciation for the sponsors of Dolphin 2.9:

• Crusoe Cloud - provided excellent on-demand 8xH100 node

This model is based on Dolphin-2.9-Mixtral-8x22b, and is Apache-2.0 licensed.

The base model has 64k context, and the full-weight fine-tuning was with 4k sequence length.

It took 1 week on 8xH100 provided by Crusoe Cloud

This model was trained FFT on 50% parameters (targeted with Laser Scanner by Fernando Fernandes, David Golchinfar, Lucas Atkins, and Eric Hartford) , 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 has a variety of instruction, conversational, and coding skills. It also has initial agentic abilities and supports function calling.

Dolphin is uncensored. I 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 Apache 2.0. I grant permission for any use, including commercial, that falls within accordance with Apache-2.0 license. Dolphin was trained on data generated from GPT4, among other models.

Evals

Training

See axolotl config

axolotl version: 0.4.0

base_model: mistral-community/Mixtral-8x22B-v0.1
model_type: AutoModelForCausalLM
tokenizer_type: LlamaTokenizer
trust_remote_code: true

load_in_8bit: false
load_in_4bit: false
strict: false

unfrozen_parameters:
  - ^lm_head.weight$
  - ^model.embed_tokens.weight$
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  - model.layers.1.self_attn.q_proj
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  - model.layers.27.self_attn.q_proj
  - model.layers.28.self_attn.q_proj
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  - model.layers.21.self_attn.q_proj
  - model.layers.24.self_attn.q_proj
  - model.layers.14.self_attn.q_proj
  - model.layers.15.self_attn.q_proj
  - model.layers.11.self_attn.q_proj
  - model.layers.20.self_attn.q_proj
  - model.layers.23.self_attn.q_proj
  - model.layers.30.self_attn.k_proj
  - model.layers.31.self_attn.k_proj
  - model.layers.25.self_attn.k_proj
  - model.layers.23.self_attn.k_proj
  - model.layers.27.self_attn.k_proj
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  - model.layers.16.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.6.self_attn.k_proj
  - model.layers.22.self_attn.v_proj
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  - model.layers.5.self_attn.v_proj
  - model.layers.8.self_attn.v_proj
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  - model.layers.9.self_attn.v_proj
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  - model.layers.20.self_attn.o_proj
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  - model.layers.7.block_sparse_moe.experts.6.w1
  - model.layers.8.block_sparse_moe.experts.6.w1
  - model.layers.9.block_sparse_moe.experts.6.w1
  - model.layers.10.block_sparse_moe.experts.6.w1
  - model.layers.11.block_sparse_moe.experts.6.w1
  - model.layers.12.block_sparse_moe.experts.6.w1
  - model.layers.13.block_sparse_moe.experts.6.w1
  - model.layers.5.block_sparse_moe.experts.6.w2
  - model.layers.4.block_sparse_moe.experts.6.w2
  - model.layers.2.block_sparse_moe.experts.6.w2
  - model.layers.3.block_sparse_moe.experts.6.w2
  - model.layers.1.block_sparse_moe.experts.6.w2
  - model.layers.0.block_sparse_moe.experts.6.w2
  - model.layers.6.block_sparse_moe.experts.6.w2
  - model.layers.7.block_sparse_moe.experts.6.w2
  - model.layers.8.block_sparse_moe.experts.6.w2
  - model.layers.9.block_sparse_moe.experts.6.w2
  - model.layers.10.block_sparse_moe.experts.6.w2
  - model.layers.11.block_sparse_moe.experts.6.w2
  - model.layers.12.block_sparse_moe.experts.6.w2
  - model.layers.13.block_sparse_moe.experts.6.w2
  - model.layers.5.block_sparse_moe.experts.6.w3
  - model.layers.4.block_sparse_moe.experts.6.w3
  - model.layers.3.block_sparse_moe.experts.6.w3
  - model.layers.2.block_sparse_moe.experts.6.w3
  - model.layers.1.block_sparse_moe.experts.6.w3
  - model.layers.0.block_sparse_moe.experts.6.w3
  - model.layers.6.block_sparse_moe.experts.6.w3
  - model.layers.7.block_sparse_moe.experts.6.w3
  - model.layers.8.block_sparse_moe.experts.6.w3
  - model.layers.9.block_sparse_moe.experts.6.w3
  - model.layers.10.block_sparse_moe.experts.6.w3
  - model.layers.11.block_sparse_moe.experts.6.w3
  - model.layers.12.block_sparse_moe.experts.6.w3
  - model.layers.13.block_sparse_moe.experts.6.w3
  - model.layers.5.block_sparse_moe.experts.7.w1
  - model.layers.6.block_sparse_moe.experts.7.w1
  - model.layers.3.block_sparse_moe.experts.7.w1
  - model.layers.4.block_sparse_moe.experts.7.w1
  - model.layers.2.block_sparse_moe.experts.7.w1
  - model.layers.0.block_sparse_moe.experts.7.w1
  - model.layers.7.block_sparse_moe.experts.7.w1
  - model.layers.8.block_sparse_moe.experts.7.w1
  - model.layers.9.block_sparse_moe.experts.7.w1
  - model.layers.10.block_sparse_moe.experts.7.w1
  - model.layers.11.block_sparse_moe.experts.7.w1
  - model.layers.12.block_sparse_moe.experts.7.w1
  - model.layers.13.block_sparse_moe.experts.7.w1
  - model.layers.14.block_sparse_moe.experts.7.w1
  - model.layers.6.block_sparse_moe.experts.7.w2
  - model.layers.5.block_sparse_moe.experts.7.w2
  - model.layers.4.block_sparse_moe.experts.7.w2
  - model.layers.2.block_sparse_moe.experts.7.w2
  - model.layers.3.block_sparse_moe.experts.7.w2
  - model.layers.1.block_sparse_moe.experts.7.w2
  - model.layers.0.block_sparse_moe.experts.7.w2
  - model.layers.7.block_sparse_moe.experts.7.w2
  - model.layers.8.block_sparse_moe.experts.7.w2
  - model.layers.9.block_sparse_moe.experts.7.w2
  - model.layers.10.block_sparse_moe.experts.7.w2
  - model.layers.11.block_sparse_moe.experts.7.w2
  - model.layers.12.block_sparse_moe.experts.7.w2
  - model.layers.13.block_sparse_moe.experts.7.w2
  - model.layers.6.block_sparse_moe.experts.7.w3
  - model.layers.5.block_sparse_moe.experts.7.w3
  - model.layers.4.block_sparse_moe.experts.7.w3
  - model.layers.3.block_sparse_moe.experts.7.w3
  - model.layers.2.block_sparse_moe.experts.7.w3
  - model.layers.0.block_sparse_moe.experts.7.w3
  - model.layers.7.block_sparse_moe.experts.7.w3
  - model.layers.8.block_sparse_moe.experts.7.w3
  - model.layers.9.block_sparse_moe.experts.7.w3
  - model.layers.10.block_sparse_moe.experts.7.w3
  - model.layers.11.block_sparse_moe.experts.7.w3
  - model.layers.12.block_sparse_moe.experts.7.w3
  - model.layers.13.block_sparse_moe.experts.7.w3
  - model.layers.14.block_sparse_moe.experts.7.w3
  - model.layers.0.block_sparse_moe.gate
  - model.layers.1.block_sparse_moe.gate
  - model.layers.2.block_sparse_moe.gate
  - model.layers.3.block_sparse_moe.gate
  - model.layers.4.block_sparse_moe.gate
  - model.layers.5.block_sparse_moe.gate
  - model.layers.6.block_sparse_moe.gate
  - model.layers.7.block_sparse_moe.gate
  - model.layers.8.block_sparse_moe.gate
  - model.layers.9.block_sparse_moe.gate
  - model.layers.10.block_sparse_moe.gate
  - model.layers.11.block_sparse_moe.gate
  - model.layers.12.block_sparse_moe.gate
  - model.layers.13.block_sparse_moe.gate
  
model_config:
  output_router_logits: true

datasets:
  - path: /workspace/datasets/dolphin-2.9/dolphin201-sharegpt2.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/Ultrachat200kunfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/dolphin-coder-translate-sharegpt2.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/dolphin-coder-codegen-sharegpt2.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/m-a-p_Code-Feedback-sharegpt-unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/m-a-p_CodeFeedback-Filtered-Instruction-sharegpt-unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/not_samantha_norefusals.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/Orca-Math-resort-unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/agent_instruct_react_unfiltered.jsonl
    type: sharegpt  
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/toolbench_instruct_j1s1_3k_unfiltered.jsonl
    type: sharegpt  
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/toolbench_negative_unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/toolbench_react_10p_unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/toolbench_tflan_cot_30p_unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/openhermes200k_unfiltered.jsonl
    type: sharegpt 
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/SystemConversations.jsonl
    type: sharegpt
    conversation: chatml

chat_template: chatml

dataset_prepared_path: thingy
val_set_size: 0.0002
output_dir: ./out

sequence_len: 4096
sample_packing: true
pad_to_sequence_len: true

gradient_accumulation_steps: 8
micro_batch_size: 4
num_epochs: 3
logging_steps: 1
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 2.7e-5

wandb_project: dolphin-2.9-mixtral-8x22b
wandb_watch:
wandb_run_id:
wandb_log_model:

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

gradient_checkpointing: true
gradient_checkpointing_kwargs:
  use_reentrant: false
early_stopping_patience:
# resume_from_checkpoint: /home/ehartford/axolotl/out/checkpoint-316
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
saves_per_epoch: 8
save_total_limit: 2
save_steps:
evals_per_epoch: 4
eval_sample_packing: false
debug:
deepspeed: deepspeed_configs/zero3_bf16_cpuoffload_params.json
weight_decay: 0.05
fsdp:
fsdp_config:
special_tokens:
  eos_token: "<|im_end|>"
tokens:
  - "<|im_start|>"

Training results

Training Loss	Epoch	Step	Validation Loss
0.7022	0.0	1	0.6989
0.5344	0.25	238	0.5138
0.5204	0.5	476	0.5018
0.5059	0.75	714	0.4951
0.5112	1.0	952	0.4911
0.4561	1.24	1190	0.4978
0.478	1.49	1428	0.4935
0.4714	1.74	1666	0.4899
0.4626	1.99	1904	0.4861
0.3675	2.22	2142	0.5240
0.3595	2.47	2380	0.5229
0.3438	2.72	2618	0.5217

Framework versions

• Transformers 4.40.0.dev0
• Pytorch 2.2.2+cu121
• Datasets 2.15.0
• Tokenizers 0.15.0