base_model: axolotl-ai-co/Mistral-Small-4-119B-2603-BF16

plugins:
  - axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin

load_in_4bit: true
quantize_moe_experts: true

datasets:
  - path: fozziethebeat/alpaca_messages_2k_test
    type: chat_template

dataset_prepared_path: last_run_prepared
val_set_size: 0.01
output_dir: ./outputs/out

adapter: qlora

sequence_len: 2048
sample_packing: true

lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_modules: 'model.language_model.layers.[\d]+.(mlp|cross_attn|self_attn).(up|down|gate|q|k|v|o)_proj'

# uncomment to train on expert layers
# lora_target_parameters:
#   - mlp.experts.gate_up_proj
#   - mlp.experts.down_proj
# lora_mlp_kernel: false
# lora_qkv_kernel: false
# lora_o_kernel: false

wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:

gradient_accumulation_steps: 1
micro_batch_size: 1
num_epochs: 1
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0002

bf16: true
tf32: true

gradient_checkpointing: true
logging_steps: 1
flash_attention: true

warmup_ratio: 0.1
evals_per_epoch: 1
saves_per_epoch: 1
weight_decay: 0.0