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dolphin-2.9.3-mistral-nemo-12b

cognitivecomputations / dolphin-2.9.3-mistral-nemo-12b

Run on huggingface.co
huggingface.co
Total runs: 3.2K
24-hour runs: 0
7-day runs: 0
30-day runs: 0
Model's Last Updated: July 26 2024
text-generation

Introduction of dolphin-2.9.3-mistral-nemo-12b

Model Details of dolphin-2.9.3-mistral-nemo-12b

Dolphin 2.9.3 Mistral Nemo 12b 🐬

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:

This model is based on mistralai/Mistral-Nemo-Base-2407, and is governed by the apache 2.0 license.

The base model has 128K context, and our finetuning used 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
See evals 
|                           Tasks                           |Version|Filter|n-shot|        Metric         |   |Value |   |Stderr|
|-----------------------------------------------------------|-------|------|-----:|-----------------------|---|-----:|---|------|
|leaderboard                                                |N/A    |none  |     0|acc                    |↑  |0.3437|±  |0.0043|
|                                                           |       |none  |     0|acc_norm               |↑  |0.5076|±  |0.0053|
|                                                           |       |none  |     0|exact_match            |↑  |0.0536|±  |0.0061|
|                                                           |       |none  |     0|inst_level_loose_acc   |↑  |0.4388|±  |N/A   |
|                                                           |       |none  |     0|inst_level_strict_acc  |↑  |0.3741|±  |N/A   |
|                                                           |       |none  |     0|prompt_level_loose_acc |↑  |0.3105|±  |0.0199|
|                                                           |       |none  |     0|prompt_level_strict_acc|↑  |0.2477|±  |0.0186|
| - leaderboard_bbh                                         |N/A    |none  |     3|acc_norm               |↑  |0.5549|±  |0.0061|
|  - leaderboard_bbh_boolean_expressions                    |      0|none  |     3|acc_norm               |↑  |0.8640|±  |0.0217|
|  - leaderboard_bbh_causal_judgement                       |      0|none  |     3|acc_norm               |↑  |0.6417|±  |0.0352|
|  - leaderboard_bbh_date_understanding                     |      0|none  |     3|acc_norm               |↑  |0.6080|±  |0.0309|
|  - leaderboard_bbh_disambiguation_qa                      |      0|none  |     3|acc_norm               |↑  |0.6480|±  |0.0303|
|  - leaderboard_bbh_formal_fallacies                       |      0|none  |     3|acc_norm               |↑  |0.5360|±  |0.0316|
|  - leaderboard_bbh_geometric_shapes                       |      0|none  |     3|acc_norm               |↑  |0.5240|±  |0.0316|
|  - leaderboard_bbh_hyperbaton                             |      0|none  |     3|acc_norm               |↑  |0.6440|±  |0.0303|
|  - leaderboard_bbh_logical_deduction_five_objects         |      0|none  |     3|acc_norm               |↑  |0.4600|±  |0.0316|
|  - leaderboard_bbh_logical_deduction_seven_objects        |      0|none  |     3|acc_norm               |↑  |0.4680|±  |0.0316|
|  - leaderboard_bbh_logical_deduction_three_objects        |      0|none  |     3|acc_norm               |↑  |0.7000|±  |0.0290|
|  - leaderboard_bbh_movie_recommendation                   |      0|none  |     3|acc_norm               |↑  |0.8160|±  |0.0246|
|  - leaderboard_bbh_navigate                               |      0|none  |     3|acc_norm               |↑  |0.6040|±  |0.0310|
|  - leaderboard_bbh_object_counting                        |      0|none  |     3|acc_norm               |↑  |0.3680|±  |0.0306|
|  - leaderboard_bbh_penguins_in_a_table                    |      0|none  |     3|acc_norm               |↑  |0.5548|±  |0.0413|
|  - leaderboard_bbh_reasoning_about_colored_objects        |      0|none  |     3|acc_norm               |↑  |0.6320|±  |0.0306|
|  - leaderboard_bbh_ruin_names                             |      0|none  |     3|acc_norm               |↑  |0.7440|±  |0.0277|
|  - leaderboard_bbh_salient_translation_error_detection    |      0|none  |     3|acc_norm               |↑  |0.5280|±  |0.0316|
|  - leaderboard_bbh_snarks                                 |      0|none  |     3|acc_norm               |↑  |0.6292|±  |0.0363|
|  - leaderboard_bbh_sports_understanding                   |      0|none  |     3|acc_norm               |↑  |0.8040|±  |0.0252|
|  - leaderboard_bbh_temporal_sequences                     |      0|none  |     3|acc_norm               |↑  |0.4680|±  |0.0316|
|  - leaderboard_bbh_tracking_shuffled_objects_five_objects |      0|none  |     3|acc_norm               |↑  |0.2160|±  |0.0261|
|  - leaderboard_bbh_tracking_shuffled_objects_seven_objects|      0|none  |     3|acc_norm               |↑  |0.1160|±  |0.0203|
|  - leaderboard_bbh_tracking_shuffled_objects_three_objects|      0|none  |     3|acc_norm               |↑  |0.3000|±  |0.0290|
|  - leaderboard_bbh_web_of_lies                            |      0|none  |     3|acc_norm               |↑  |0.4880|±  |0.0317|
| - leaderboard_gpqa                                        |N/A    |none  |     0|acc_norm               |↑  |0.3146|±  |0.0135|
|  - leaderboard_gpqa_diamond                               |      1|none  |     0|acc_norm               |↑  |0.3182|±  |0.0332|
|  - leaderboard_gpqa_extended                              |      1|none  |     0|acc_norm               |↑  |0.3187|±  |0.0200|
|  - leaderboard_gpqa_main                                  |      1|none  |     0|acc_norm               |↑  |0.3080|±  |0.0218|
| - leaderboard_ifeval                                      |      2|none  |     0|inst_level_loose_acc   |↑  |0.4388|±  |N/A   |
|                                                           |       |none  |     0|inst_level_strict_acc  |↑  |0.3741|±  |N/A   |
|                                                           |       |none  |     0|prompt_level_loose_acc |↑  |0.3105|±  |0.0199|
|                                                           |       |none  |     0|prompt_level_strict_acc|↑  |0.2477|±  |0.0186|
|  - leaderboard_math_algebra_hard                          |      1|none  |     4|exact_match            |↑  |0.0749|±  |0.0150|
|  - leaderboard_math_counting_and_prob_hard                |      1|none  |     4|exact_match            |↑  |0.0244|±  |0.0140|
|  - leaderboard_math_geometry_hard                         |      1|none  |     4|exact_match            |↑  |0.0227|±  |0.0130|
| - leaderboard_math_hard                                   |N/A    |none  |     4|exact_match            |↑  |0.0536|±  |0.0061|
|  - leaderboard_math_intermediate_algebra_hard             |      1|none  |     4|exact_match            |↑  |0.0250|±  |0.0093|
|  - leaderboard_math_num_theory_hard                       |      1|none  |     4|exact_match            |↑  |0.0390|±  |0.0156|
|  - leaderboard_math_prealgebra_hard                       |      1|none  |     4|exact_match            |↑  |0.1295|±  |0.0242|
|  - leaderboard_math_precalculus_hard                      |      1|none  |     4|exact_match            |↑  |0.0296|±  |0.0146|
| - leaderboard_mmlu_pro                                    |    0.1|none  |     5|acc                    |↑  |0.3437|±  |0.0043|
| - leaderboard_musr                                        |N/A    |none  |     0|acc_norm               |↑  |0.4511|±  |0.0178|
|  - leaderboard_musr_murder_mysteries                      |      1|none  |     0|acc_norm               |↑  |0.5880|±  |0.0312|
|  - leaderboard_musr_object_placements                     |      1|none  |     0|acc_norm               |↑  |0.3438|±  |0.0297|
|  - leaderboard_musr_team_allocation                       |      1|none  |     0|acc_norm               |↑  |0.4240|±  |0.0313|

|         Groups         |Version|Filter|n-shot|        Metric         |   |Value |   |Stderr|
|------------------------|-------|------|-----:|-----------------------|---|-----:|---|------|
|leaderboard             |N/A    |none  |     0|acc                    |↑  |0.3437|±  |0.0043|
|                        |       |none  |     0|acc_norm               |↑  |0.5076|±  |0.0053|
|                        |       |none  |     0|exact_match            |↑  |0.0536|±  |0.0061|
|                        |       |none  |     0|inst_level_loose_acc   |↑  |0.4388|±  |N/A   |
|                        |       |none  |     0|inst_level_strict_acc  |↑  |0.3741|±  |N/A   |
|                        |       |none  |     0|prompt_level_loose_acc |↑  |0.3105|±  |0.0199|
|                        |       |none  |     0|prompt_level_strict_acc|↑  |0.2477|±  |0.0186|
| - leaderboard_bbh      |N/A    |none  |     3|acc_norm               |↑  |0.5549|±  |0.0061|
| - leaderboard_gpqa     |N/A    |none  |     0|acc_norm               |↑  |0.3146|±  |0.0135|
| - leaderboard_math_hard|N/A    |none  |     4|exact_match            |↑  |0.0536|±  |0.0061|
| - leaderboard_musr     |N/A    |none  |     0|acc_norm               |↑  |0.4511|±  |0.0178|

Training

Built with Axolotl

See axolotl config

axolotl version: 0.4.1 

base_model: /workspace/models/Mistral-Nemo-Base-2407
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


unfrozen_parameters:
- ^lm_head.weight$
- ^model.embed_tokens.weight$
- input_layernorm
- model.norm
- post_attention_layernorm
- self_attn.rotary_emb
# mlp.down_proj layers
- model.layers.0.mlp.down_proj
- model.layers.1.mlp.down_proj
- model.layers.4.mlp.down_proj
- model.layers.37.mlp.down_proj
- model.layers.24.mlp.down_proj
- model.layers.2.mlp.down_proj
- model.layers.38.mlp.down_proj
- model.layers.35.mlp.down_proj
- model.layers.25.mlp.down_proj
- model.layers.6.mlp.down_proj
- model.layers.22.mlp.down_proj
- model.layers.23.mlp.down_proj
- model.layers.3.mlp.down_proj
- model.layers.21.mlp.down_proj
- model.layers.5.mlp.down_proj
- model.layers.28.mlp.down_proj
- model.layers.20.mlp.down_proj
- model.layers.26.mlp.down_proj
- model.layers.19.mlp.down_proj
- model.layers.34.mlp.down_proj
# mlp.gate_proj layers
- model.layers.2.mlp.gate_proj
- model.layers.1.mlp.gate_proj
- model.layers.3.mlp.gate_proj
- model.layers.5.mlp.gate_proj
- model.layers.4.mlp.gate_proj
- model.layers.35.mlp.gate_proj
- model.layers.36.mlp.gate_proj
- model.layers.37.mlp.gate_proj
- model.layers.38.mlp.gate_proj
- model.layers.34.mlp.gate_proj
- model.layers.33.mlp.gate_proj
- model.layers.8.mlp.gate_proj
- model.layers.32.mlp.gate_proj
- model.layers.6.mlp.gate_proj
- model.layers.28.mlp.gate_proj
- model.layers.26.mlp.gate_proj
- model.layers.30.mlp.gate_proj
- model.layers.23.mlp.gate_proj
- model.layers.29.mlp.gate_proj
- model.layers.27.mlp.gate_proj
# mlp.up_proj layers
- model.layers.3.mlp.up_proj
- model.layers.4.mlp.up_proj
- model.layers.6.mlp.up_proj
- model.layers.2.mlp.up_proj
- model.layers.5.mlp.up_proj
- model.layers.8.mlp.up_proj
- model.layers.10.mlp.up_proj
- model.layers.9.mlp.up_proj
- model.layers.7.mlp.up_proj
- model.layers.0.mlp.up_proj
- model.layers.17.mlp.up_proj
- model.layers.15.mlp.up_proj
- model.layers.22.mlp.up_proj
- model.layers.18.mlp.up_proj
- model.layers.16.mlp.up_proj
- model.layers.11.mlp.up_proj
- model.layers.21.mlp.up_proj
- model.layers.23.mlp.up_proj
- model.layers.20.mlp.up_proj
- model.layers.27.mlp.up_proj
# self_attn.k_proj layers
- model.layers.30.self_attn.k_proj
- model.layers.27.self_attn.k_proj
- model.layers.25.self_attn.k_proj
- model.layers.33.self_attn.k_proj
- model.layers.26.self_attn.k_proj
- model.layers.31.self_attn.k_proj
- model.layers.35.self_attn.k_proj
- model.layers.39.self_attn.k_proj
- model.layers.22.self_attn.k_proj
- model.layers.24.self_attn.k_proj
- model.layers.21.self_attn.k_proj
- model.layers.28.self_attn.k_proj
- model.layers.23.self_attn.k_proj
- model.layers.36.self_attn.k_proj
- model.layers.20.self_attn.k_proj
- model.layers.37.self_attn.k_proj
- model.layers.29.self_attn.k_proj
- model.layers.32.self_attn.k_proj
- model.layers.16.self_attn.k_proj
- model.layers.18.self_attn.k_proj
# self_attn.o_proj layers
- model.layers.7.self_attn.o_proj
- model.layers.6.self_attn.o_proj
- model.layers.9.self_attn.o_proj
- model.layers.5.self_attn.o_proj
- model.layers.27.self_attn.o_proj
- model.layers.26.self_attn.o_proj
- model.layers.4.self_attn.o_proj
- model.layers.31.self_attn.o_proj
- model.layers.8.self_attn.o_proj
- model.layers.16.self_attn.o_proj
- model.layers.3.self_attn.o_proj
- model.layers.10.self_attn.o_proj
- model.layers.18.self_attn.o_proj
- model.layers.33.self_attn.o_proj
- model.layers.17.self_attn.o_proj
- model.layers.32.self_attn.o_proj
- model.layers.30.self_attn.o_proj
- model.layers.2.self_attn.o_proj
- model.layers.15.self_attn.o_proj
- model.layers.11.self_attn.o_proj
# self_attn.q_proj layers
- model.layers.14.self_attn.q_proj
- model.layers.11.self_attn.q_proj
- model.layers.15.self_attn.q_proj
- model.layers.9.self_attn.q_proj
- model.layers.8.self_attn.q_proj
- model.layers.18.self_attn.q_proj
- model.layers.12.self_attn.q_proj
- model.layers.13.self_attn.q_proj
- model.layers.19.self_attn.q_proj
- model.layers.16.self_attn.q_proj
- model.layers.10.self_attn.q_proj
- model.layers.17.self_attn.q_proj
- model.layers.7.self_attn.q_proj
- model.layers.5.self_attn.q_proj
- model.layers.20.self_attn.q_proj
- model.layers.3.self_attn.q_proj
- model.layers.26.self_attn.q_proj
- model.layers.27.self_attn.q_proj
- model.layers.28.self_attn.q_proj
- model.layers.33.self_attn.q_proj
# self_attn.v_proj layers
- model.layers.27.self_attn.v_proj
- model.layers.20.self_attn.v_proj
- model.layers.24.self_attn.v_proj
- model.layers.25.self_attn.v_proj
- model.layers.30.self_attn.v_proj
- model.layers.2.self_attn.v_proj
- model.layers.23.self_attn.v_proj
- model.layers.22.self_attn.v_proj
- model.layers.26.self_attn.v_proj
- model.layers.33.self_attn.v_proj
- model.layers.37.self_attn.v_proj
- model.layers.7.self_attn.v_proj
- model.layers.4.self_attn.v_proj
- model.layers.18.self_attn.v_proj
- model.layers.31.self_attn.v_proj
- model.layers.17.self_attn.v_proj
- model.layers.35.self_attn.v_proj
- model.layers.32.self_attn.v_proj
- model.layers.21.self_attn.v_proj
- model.layers.3.self_attn.v_proj



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

sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true

wandb_project: dolphin-2.9.3-Mistral-nemo
wandb_watch:
wandb_run_id:
wandb_log_model:

gradient_accumulation_steps: 16
micro_batch_size: 1
num_epochs: 3
optimizer: adamw_torch
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: deepspeed_configs/zero3_bf16.json
weight_decay: 0.1
special_tokens:
  eos_token: "<|im_end|>"
  pad_token: "<pad>"
  bos_token: "<s>"
  unk_token: "<unk>"
tokens:
  - "<|im_start|>"


# fsdp:
#   - full_shard
#   - auto_wrap
# fsdp_config:
#   fsdp_limit_all_gathers: true
#   fsdp_sync_module_states: true
#   fsdp_offload_params: true
#   fsdp_use_orig_params: false
#   fsdp_cpu_ram_efficient_loading: true
#   fsdp_transformer_layer_cls_to_wrap: MixtralSparseMoeBlock
#   fsdp_state_dict_type: FULL_STATE_DICT
#   fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
#   fsdp_sharding_strategy: FULL_SHARD
#   fsdp_forward_prefetch: false
#   fsdp_backward_prefetch: BACKWARD_PRE

Visualize in Weights & Biases

workspace/axolotl/dolphin-2.9.3-mistral-nemo

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5605
Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure
Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-06
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 128
  • total_eval_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 3
Training results
Training Loss Epoch Step Validation Loss
0.5691 1.0162 983 0.5734
0.5335 2.0174 1968 0.5609
0.5297 2.9639 2901 0.5605
Framework versions
  • Transformers 4.43.0.dev0
  • Pytorch 2.2.2+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1

Runs of cognitivecomputations dolphin-2.9.3-mistral-nemo-12b on huggingface.co

3.2K
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
0
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More Information About dolphin-2.9.3-mistral-nemo-12b huggingface.co Model

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https://choosealicense.com/licenses/apache-2.0

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dolphin-2.9.3-mistral-nemo-12b huggingface.co is an AI model on huggingface.co that provides dolphin-2.9.3-mistral-nemo-12b's model effect (), which can be used instantly with this cognitivecomputations dolphin-2.9.3-mistral-nemo-12b model. huggingface.co supports a free trial of the dolphin-2.9.3-mistral-nemo-12b model, and also provides paid use of the dolphin-2.9.3-mistral-nemo-12b. Support call dolphin-2.9.3-mistral-nemo-12b model through api, including Node.js, Python, http.

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dolphin-2.9.3-mistral-nemo-12b install

dolphin-2.9.3-mistral-nemo-12b is an open source model from GitHub that offers a free installation service, and any user can find dolphin-2.9.3-mistral-nemo-12b on GitHub to install. At the same time, huggingface.co provides the effect of dolphin-2.9.3-mistral-nemo-12b install, users can directly use dolphin-2.9.3-mistral-nemo-12b installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

dolphin-2.9.3-mistral-nemo-12b install url in huggingface.co:

https://huggingface.co/cognitivecomputations/dolphin-2.9.3-mistral-nemo-12b

Url of dolphin-2.9.3-mistral-nemo-12b

Provider of dolphin-2.9.3-mistral-nemo-12b huggingface.co

cognitivecomputations
ORGANIZATIONS
huggingface.co

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