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magistrate-3.2-3b-it

Text Generation
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English
llama
spectrum
llama-3
axolotl
legal
HFforLegal
conversational
text-generation-inference
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metadata
language:
  - en
license: llama3.2
library_name: transformers
tags:
  - spectrum
  - llama-3
  - axolotl
  - legal
  - HFforLegal
base_model: macadeliccc/magistrate-3.2-3b-base
datasets:
  - teknium/OpenHermes-2.5
  - NousResearch/hermes-function-calling-v1
  - arcee-ai/The-Tome
  - cognitivecomputations/SystemChat-2.0
pipeline_tag: text-generation
model-index:
  - name: magistrate-3.2-3b-it
    results:
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: IFEval (0-Shot)
          type: HuggingFaceH4/ifeval
          args:
            num_few_shot: 0
        metrics:
          - type: inst_level_strict_acc and prompt_level_strict_acc
            value: 22.92
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=macadeliccc/magistrate-3.2-3b-it
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: BBH (3-Shot)
          type: BBH
          args:
            num_few_shot: 3
        metrics:
          - type: acc_norm
            value: 5.32
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=macadeliccc/magistrate-3.2-3b-it
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MATH Lvl 5 (4-Shot)
          type: hendrycks/competition_math
          args:
            num_few_shot: 4
        metrics:
          - type: exact_match
            value: 1.59
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=macadeliccc/magistrate-3.2-3b-it
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: GPQA (0-shot)
          type: Idavidrein/gpqa
          args:
            num_few_shot: 0
        metrics:
          - type: acc_norm
            value: 0
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=macadeliccc/magistrate-3.2-3b-it
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MuSR (0-shot)
          type: TAUR-Lab/MuSR
          args:
            num_few_shot: 0
        metrics:
          - type: acc_norm
            value: 5.74
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=macadeliccc/magistrate-3.2-3b-it
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MMLU-PRO (5-shot)
          type: TIGER-Lab/MMLU-Pro
          config: main
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 6.58
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=macadeliccc/magistrate-3.2-3b-it
          name: Open LLM Leaderboard

magistrate-3.2-3b-it

This model is a fine-tuned version of macadeliccc/magistrate-3.2-3b-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8067

Built with Axolotl

See axolotl config

axolotl version: 0.4.1

base_model: macadeliccc/magistrate-3.2-3b-base
model_type: LlamaForCausalLM
tokenizer_type: AutoTokenizer

load_in_8bit: false
load_in_4bit: false
strict: false

datasets:
  - path: json 
    type: sharegpt
    conversation: chatml
    data_files: train/hermes-2.5.jsonl
  # - path: json 
  #   type: sharegpt
  #   conversation: chatml
  #   data_files: train/financial_instructions_cleaned_2.json
  - path: json 
    type: sharegpt
    conversation: chatml
    data_files: train/glaive-function-calling-5k.json
  - path: json 
    type: sharegpt
    conversation: chatml
    data_files: train/func-calling-singleturn.json
  - path: json 
    type: sharegpt
    conversation: chatml
    data_files: train/func-calling.json
  - path: json 
    type: sharegpt
    conversation: chatml
    data_files: train/json-mode-agentic.json
  - path: json 
    type: sharegpt
    conversation: chatml
    data_files: train/json-mode-singleturn.json
  - path: json 
    type: sharegpt
    conversation: chatml
    data_files: train/reasoning_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/systemchat_2_0_small.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/303_creative_llc_v__elenis_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/abitron_austria_gmbh_v__hetronic_international__inc__sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/acheson_hotels__llc_v__laufer_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/alexander_v__sc_conference_of_naacp_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/amgen_inc__v__sanofi_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/andy_warhol_found___inc__v__goldsmith_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/arizona_v__navajo_nation_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/becerra__sec__of_h_hs_v__san_carlos_apache_tribe_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/biden_v__nebraska_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/bissonnette_v__lepage_bakeries_park_st___llc_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/bittner_v__united_states_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/brown_v__united_states_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/cantero_v__bank_of_america__n_a__sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/cfpb_v__com__fin__services_assn__sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/chiaverini_v__city_of_napoleon_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/ciminelli_v__united_state_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/city_of_grants_pass_v__johnson_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/coinbase__inc__v__bielski_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/coinbase__inc__v__suski_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/connelly_v__united_states_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/corner_post__inc__v__bd__of_governors__frs_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/counterman_v__colorado_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/cruz_v__arizona_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/culley_v__marshall_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/dept__of_agric__rural_dev__v__kirtz_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/dept__of_education_v__brown_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/dept__of_state_v__munoz_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/devillier_v__texas_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/diaz_v__united_states_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/dubin_v__united_states_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/dupree_v__younger_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/erlinger_v__united_states_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/fbi_v__fikre_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/fda_v__alliance_hippocratic_medicine_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/financial_oversight_board_v__cpi_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/fischer_v__united_states_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/garland__att_y_gen__v__cargill_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/glacier_northwest__inc__v__int_l_brotherhood_of_teamsters_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/gonzalez_v__google_llc_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/gonzalez_v__trevino_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/great_lakes_insurance_se_v__raiders_retreat_realty_co___llc_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/groff_v__dejoy_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/harrington_v__purdue_pharma_l_p__sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/harrow_v__dept__of_defense_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/health_and_hospital_corp__v__talevski_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/helix_energy_solutions_v__hewitt_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/in_re_grand_jury_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/jack_daniel_s_properties__inc__v__vip_products_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/jones_v__hendrix_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/karcho_polselli_v__irs_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/lac_du_flambeau_band_v__coughlin_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/lindke_v__freed_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/loper_bright_enterprises__inc__v__raimondo__sec__of_comm__sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/lora_v__united_states_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/macquarie_infrastructure_corp__v__moab_partners__l_p__sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/mallory_v__norfolk_southern_railway_co__sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/mcintosh_v__united_states_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/merrill_v__milligan_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/moore_v__harper_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/moore_v__united_states_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/moyle_v__united_states_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/muldrow_v__st__louis_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/murray_v__ubs_securities__llc_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/murthy__surgeon_gen__v__missouri_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/netchoice__llc_v__paxton_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/new_york_v__new_jersey_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/nra_v__vullo_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/o_connor_ratcliff_v__garnier_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/oh_adjutant_gen__s_dept__v__flra_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/ohio_v__epa_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/perez_v__sturgis_public_schools_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/pugin_v__garland_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/pulsifer_v__united_states_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/relentless__inc__v__dept__of_commerce_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/rudisill_v__mcdonough__sec__of_va_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/sackett_v__epa_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/samia_v__united_states_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/santos_zacaria_v__garland__att_y_gen__sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/sec_v__cochran_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/sec_v__jarkesy_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/sheetz_v__county_of_el_dorado_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/slack_technologies__llc_v__pirani_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/smith_v__arizona_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/smith_v__spizzirri_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/smith_v__united_states_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/snyder_v__united_states_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/starbucks_corp__v__mckinney_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/students_for_fair_admissions_v__university_of_nc_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/texas_v__new_mexico_and_colorado_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/thornell_v__jones_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/truck_insurance_exchange_v__kaiser_gypsum_co__inc__sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/trump_v__anderson_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/turkiye_halk_bankasi_a_s__v__united_states_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/twitter__inc__v__taamneh_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/tyler_v__hennepin_county_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/u_s___ex_rel__polansky_v__executive_health_sharegpt.json
  - path: json
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    conversation: chatml
    data_files: train/argument_dataset/u_s___ex_rel__schutte_v__supervalu_inc__sharegpt.json
  - path: json
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    conversation: chatml
    data_files: train/argument_dataset/united_states_trustee_v__john_q__hammons_fall_2006__llc_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/united_states_v__hansen_sharegpt.json
  - path: json
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    conversation: chatml
    data_files: train/argument_dataset/united_states_v__rahimi_sharegpt.json
  - path: json
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    conversation: chatml
    data_files: train/argument_dataset/united_states_v__texas_sharegpt.json
  - path: json
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    conversation: chatml
    data_files: train/argument_dataset/vidal__under_sec__of_comm__v__elster_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/warner_chappell_music__inc__v__nealy_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/wilkins_v__united_states_sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/wilkinson_v__garland__att_y_gen__sharegpt.json
  - path: json
    type: sharegpt
    conversation: chatml
    data_files: train/argument_dataset/yegiazaryan_v__smagin_sharegpt.json

chat_template: chatml

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

val_set_size: 0.05
output_dir: ./outputs/magistrate-3.2-3b

sequence_len: 8192
sample_packing: true
eval_sample_packing: false
pad_to_sequence_len: true

adapter: 

wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:

gradient_accumulation_steps: 8
micro_batch_size: 1
num_epochs: 3
optimizer: paged_adamw_32bit
lr_scheduler: cosine
learning_rate: 2e-4

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
s2_attention:

warmup_steps: 1000
evals_per_epoch: 2
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 1
debug:
deepspeed: deepspeed_configs/zero3.json
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
  eos_token: "<|im_end|>"
  pad_token: "<|end_of_text|>"
tokens:
  - "<|im_start|>"
  - "<|im_end|>"

Model description

Magistrate-3.2-3b-it is a legal assistant specializing in US Supreme Court case law and US Federal regulations.

The base model is pretrained with ~250M tokens containing no synthetic legal data. The instruct model does contain synthetic data.

Intended uses & limitations

This model is for research purposes and for continued development of the legal specialty. You are liable for all model outputs.

Training and evaluation data

This model was trained on a variety of standard open source datasets like OpenHermes-2.5, hermes-function-calling, and some select entries from the Tome. Additionally, I have included a comprehensive, non-synthetic argument dataset. This is a work in progress but has shown promising results so far.

Training procedure

Spectrum top 35% finetune for both pretrain and SFT. Thanks to the cognitive computations team for the work done with spectrum.

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0002
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 2
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 16
  • total_eval_batch_size: 2
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss
1.3754 0.0005 1 1.7429
1.0 0.5002 1017 0.8864
0.9482 1.0005 2034 0.8395
0.6817 1.4987 3051 0.8063
0.697 1.9991 4068 0.7580
0.3769 2.4966 5085 0.8140
0.4278 2.9965 6102 0.8067

Framework versions

  • Transformers 4.45.0
  • Pytorch 2.3.1+cu121
  • Datasets 2.21.0
  • Tokenizers 0.20.0

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 7.03
IFEval (0-Shot) 22.92
BBH (3-Shot) 5.32
MATH Lvl 5 (4-Shot) 1.59
GPQA (0-shot) 0.00
MuSR (0-shot) 5.74
MMLU-PRO (5-shot) 6.58