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This is a uncenscored version of Phi-3.

Abliterated using the following the guide here: https://huggingface.co/blog/mlabonne/abliteration

Then it was fine tuned on orpo-dpo-mix-40k

Built with Axolotl

See axolotl config

axolotl version: 0.4.0

base_model: cowWhySo/Phi-3-mini-4k-instruct-Friendly
trust_remote_code: true
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
chat_template: phi_3

load_in_8bit: false
load_in_4bit: true
strict: false
save_safetensors: true

rl: dpo
datasets:
  - path: mlabonne/orpo-dpo-mix-40k
    split: train
    type: chatml.intel

dataset_prepared_path:
val_set_size: 0.0
output_dir: ./out

sequence_len: 4096
sample_packing: false
pad_to_sequence_len: false

adapter: qlora
lora_model_dir:

lora_r: 64
lora_alpha: 32
lora_dropout: 0.1
lora_target_linear: true
lora_fan_in_fan_out:

wandb_project: axolotl
wandb_entity:
wandb_watch:
wandb_name: phi3-mini-4k-instruct-Friendly
wandb_log_model:

gradient_accumulation_steps: 8
micro_batch_size: 4
num_epochs: 1
optimizer: paged_adamw_8bit
lr_scheduler: linear
learning_rate: 5e-6
train_on_inputs: false
group_by_length: false

bf16: auto

gradient_checkpointing: true
gradient_checkpointing_kwargs:
  use_reentrant: True
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
warmup_steps: 150
evals_per_epoch: 0
eval_table_size:
eval_table_max_new_tokens: 128
saves_per_epoch: 1
debug:
deepspeed: deepspeed_configs/zero3.json
weight_decay: 0.01
max_grad_norm: 1.0
resize_token_embeddings_to_32x: true

Quants

GGUF: https://huggingface.co/cowWhySo/Phi-3-mini-4k-instruct-Friendly-gguf

Benchmarks

Model AGIEval GPT4All TruthfulQA Bigbench Average
Phi-3-mini-4k-instruct-Friendly 41 67.56 46.36 39.3 48.56

AGIEval

Task Version Metric Value Stderr
agieval_aqua_rat 0 acc 22.05 ± 2.61
acc_norm 22.05 ± 2.61
agieval_logiqa_en 0 acc 41.01 ± 1.93
acc_norm 41.32 ± 1.93
agieval_lsat_ar 0 acc 22.17 ± 2.75
acc_norm 22.17 ± 2.75
agieval_lsat_lr 0 acc 45.69 ± 2.21
acc_norm 45.88 ± 2.21
agieval_lsat_rc 0 acc 59.48 ± 3.00
acc_norm 56.51 ± 3.03
agieval_sat_en 0 acc 75.24 ± 3.01
acc_norm 70.39 ± 3.19
agieval_sat_en_without_passage 0 acc 39.81 ± 3.42
acc_norm 37.86 ± 3.39
agieval_sat_math 0 acc 33.64 ± 3.19
acc_norm 31.82 ± 3.15

Average: 41.0%

GPT4All

Task Version Metric Value Stderr
arc_challenge 0 acc 49.74 ± 1.46
acc_norm 50.43 ± 1.46
arc_easy 0 acc 76.68 ± 0.87
acc_norm 73.23 ± 0.91
boolq 1 acc 79.27 ± 0.71
hellaswag 0 acc 57.91 ± 0.49
acc_norm 77.13 ± 0.42
openbookqa 0 acc 35.00 ± 2.14
acc_norm 43.80 ± 2.22
piqa 0 acc 77.86 ± 0.97
acc_norm 79.54 ± 0.94
winogrande 0 acc 69.53 ± 1.29

Average: 67.56%

TruthfulQA

Task Version Metric Value Stderr
truthfulqa_mc 1 mc1 31.21 ± 1.62
mc2 46.36 ± 1.55

Average: 46.36%

Bigbench

Task Version Metric Value Stderr
bigbench_causal_judgement 0 multiple_choice_grade 54.74 ± 3.62
bigbench_date_understanding 0 multiple_choice_grade 66.67 ± 2.46
bigbench_disambiguation_qa 0 multiple_choice_grade 29.46 ± 2.84
bigbench_geometric_shapes 0 multiple_choice_grade 11.98 ± 1.72
exact_str_match 0.00 ± 0.00
bigbench_logical_deduction_five_objects 0 multiple_choice_grade 28.00 ± 2.01
bigbench_logical_deduction_seven_objects 0 multiple_choice_grade 17.14 ± 1.43
bigbench_logical_deduction_three_objects 0 multiple_choice_grade 45.67 ± 2.88
bigbench_movie_recommendation 0 multiple_choice_grade 24.40 ± 1.92
bigbench_navigate 0 multiple_choice_grade 53.70 ± 1.58
bigbench_reasoning_about_colored_objects 0 multiple_choice_grade 68.10 ± 1.04
bigbench_ruin_names 0 multiple_choice_grade 31.03 ± 2.19
bigbench_salient_translation_error_detection 0 multiple_choice_grade 15.93 ± 1.16
bigbench_snarks 0 multiple_choice_grade 77.35 ± 3.12
bigbench_sports_understanding 0 multiple_choice_grade 52.64 ± 1.59
bigbench_temporal_sequences 0 multiple_choice_grade 51.50 ± 1.58
bigbench_tracking_shuffled_objects_five_objects 0 multiple_choice_grade 19.52 ± 1.12
bigbench_tracking_shuffled_objects_seven_objects 0 multiple_choice_grade 13.89 ± 0.83
bigbench_tracking_shuffled_objects_three_objects 0 multiple_choice_grade 45.67 ± 2.88

Average: 39.3%

Average score: 48.56%

Training Summary

{
  "train/loss": 0.299,
  "train/grad_norm": 0.9337566701340533,
  "train/learning_rate": 0,
  "train/rewards/chosen": 0.08704188466072083,
  "train/rewards/rejected": -2.835820436477661,
  "train/rewards/accuracies": 0.84375,
  "train/rewards/margins": 2.9228620529174805,
  "train/logps/rejected": -509.9840393066406,
  "train/logps/chosen": -560.8234252929688,
  "train/logits/rejected": 1.6356163024902344,
  "train/logits/chosen": 1.7323706150054932,
  "train/epoch": 1.002169197396963,
  "train/global_step": 231,
  "_timestamp": 1717711643.3345022,
  "_runtime": 22808.557655334473,
  "_step": 231,
  "train_runtime": 22809.152,
  "train_samples_per_second": 1.944,
  "train_steps_per_second": 0.01,
  "total_flos": 0,
  "train_loss": 0.44557410065745895,
  "_wandb": {
    "runtime": 22810
  }
}
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Dataset used to train cowWhySo/Phi-3-mini-4k-instruct-Friendly