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dolphin-2.9-mixtral-8x22b
dphn/dolphin-2.9-mixtral-8x22b
dolphin-2.9-mixtral-8x22b is a text generation model from dphn. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
Curated and trained by Eric Hartford, Lucas Atkins, and Fernando Fernandes, and Cognitive Computations
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.safetensors281 GB · 100%
At a glance
- Task
- Text Generation
- Library
- transformers
- License
- apache-2.0
- Model type
- mixtral
- Access
- Public
- Created
- Apr 29, 2024
- Updated
- May 20, 2024
- SHA
- cba51344
Try a prompt
Base models
Datasets
Model card
From the Hugging Face model README
Dolphin 2.9 Mixtral 8x22b 🐬
Curated and trained by Eric Hartford, Lucas Atkins, and Fernando Fernandes, and Cognitive Computations
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
<details><summary>See axolotl config</summary>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.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
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- 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
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- model.layers.1.block_sparse_moe.experts.7.w2
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- 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
- Task
- Text Generation
- Library
- transformers
- Type
- mixtral
- License
- apache-2.0
- Languages
- en
- Created
- Apr 29, 2024
- Updated
- May 20, 2024