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Add mlflow callback for pushing config to mlflow artifacts #1125

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JohanWork
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Adding a callback to push the axolotl config to mlflow artifacts. Similare setup as exists for wandb already.

@JohanWork JohanWork changed the title Adding mlflow callback config Add mlflow callback for pushing config to mlflow artifacts Jan 15, 2024
@JohanWork JohanWork mentioned this pull request Jan 15, 2024
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@winglian
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@JohanWork do you have some screen shots to confirm verify this functionality? thanks

@JohanWork
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Sure wil add it!

@JohanWork
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JohanWork commented Jan 18, 2024

Here is screen shot, also added the config used below for reference. @winglian
Screenshot 2024-01-18 at 15 58 53

base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
model_type: LlamaForCausalLM
tokenizer_type: LlamaTokenizer
is_llama_derived_model: true

load_in_8bit: false
load_in_4bit: true
strict: false

datasets:
  - path: mhenrichsen/alpaca_2k_test
    type: alpaca
dataset_prepared_path:
val_set_size: 0.05
output_dir: ./qlora-out

adapter: qlora
lora_model_dir:

sequence_len: 1096
sample_packing: true
pad_to_sequence_len: true

lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_modules:
lora_target_linear: true
lora_fan_in_fan_out:

wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:

mlflow_experiment_name: test-test

gradient_accumulation_steps: 1
micro_batch_size: 1
num_epochs: 4
optimizer: paged_adamw_32bit
lr_scheduler: cosine
learning_rate: 0.0002

train_on_inputs: false
group_by_length: false
bf16: false
fp16: true
tf32: false

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: false

warmup_steps: 10
evals_per_epoch: 4
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:

@winglian winglian merged commit b8e5603 into axolotl-ai-cloud:main Jan 22, 2024
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