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99 3 months ago

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Dolphin 2.9.3 Mistral 7b v0.3 32k 🐬

Curated and trained by Eric Hartford and Cognitive Computations

Discord Discord: https://discord.gg/h3K4XGj2RH

Our appreciation for the sponsors of Dolphin 2.9.3: - Crusoe Cloud - provided excellent on-demand 8xH100 node - OnDemand - provided inference sponsorship

This model is based on mistralai/Mistral-7B-v0.3, and is governed by the apache 2.0 license.

The base model has 32k context, and our finetuning took place with 8192 sequence length.

Dolphin 2.9.3 uses 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-2.9.3 has a variety of instruction following, 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 apache 2.0 license. We grant permission for any use, including commercial. Dolphin was trained on data generated from GPT4, among other models.

Evals

image/png

https://huggingface.co/cognitivecomputations/dolphin-2.9.3-mistral-7B-32k

Training

Built with Axolotl

See axolotl config

axolotl version: 0.4.0 “`yaml base_model: mistralai/Mistral-7B-v0.3 model_type: AutoModelForCausalLM tokenizer_type: AutoTokenizer

load_in_8bit: false

load_in_4bit: true

strict: false

datasets: - path: /workspace/datasets/dolphin-2.9.3/dolphin201-sharegpt2.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/SystemChat_filtered_sharegpt.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/SystemChat_multilingual_sharegpt.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/dolphin-coder-translate-sharegpt2.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/dolphin-coder-codegen-sharegpt2.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/m-a-p_Code-Feedback-sharegpt-unfiltered.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/m-a-p_CodeFeedback-Filtered-Instruction-sharegpt-unfiltered.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/not_samantha_norefusals.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/Orca-Math-resort-unfiltered.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/agent_instruct_react_unfiltered.jsonl type: sharegpt
conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/toolbench_instruct_j1s1_3k_unfiltered.jsonl type: sharegpt
conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/toolbench_negative_unfiltered.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/toolbench_react_10p_unfiltered.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/toolbench_tflan_cot_30p_unfiltered.jsonl type: sharegpt conversation: chatml - path: /workspace/datasets/dolphin-2.9.3/openhermes200k_unfiltered.jsonl type: sharegpt conversation: chatml

chat_template: chatml

adapter: qlora

lora_r: 128

lora_alpha: 16

lora_modules_to_save: [embed_tokens, lm_head]

lora_dropout: 0.05

lora_target_linear: true

dataset_prepared_path: /workspace/axolotl/dolph-2.9.3-prepared val_set_size: 0.01 output_dir: /workspace/axolotl/dolphin-2.9.3-mistral-7B

sequence_len: 8192 sample_packing: true pad_to_sequence_len: true

wandb_project: dolphin-2.9.3-Mistral-7B wandb_watch: wandb_run_id: wandb_log_model:

gradient_accumulation_steps: 16 micro_batch_size: 1 num_epochs: 3 optimizer: adamw_8bit lr_scheduler: cosine learning_rate: 5e-6 train_on_inputs: false group_by_length: false bf16: auto fp16: tf32:

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: 100

evals_per_epoch: 4

eval_table_size: saves_per_epoch: 1 save_total_limit: 2 save_steps: debug: deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json weight_decay: 0.1 fsdp: fsdp_config: special_tokens: eos_token: “<|im_end|>” tokens: - “<|im_start|>”