Files
axolotl/examples/mistral/lora-mps.yml
Wing Lian af8d257aa2 make pad_to_sequence_len default to the same value as sample_packing (#2941) [skip ci]
* make pad_to_sequence_len default to the same value as sample_packing

* remove duplicate validation

* fix test

* update description meta

Co-authored-by: NanoCode012 <nano@axolotl.ai>

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Co-authored-by: NanoCode012 <nano@axolotl.ai>
2025-07-21 11:40:56 -04:00

69 lines
1.3 KiB
YAML

base_model: mistralai/Mistral-7B-v0.1
# optionally might have model_type or tokenizer_type
model_type: MistralForCausalLM
tokenizer_type: LlamaTokenizer
# Automatically upload checkpoint and final model to HF
# hub_model_id: username/custom_model_name
datasets:
- path: mhenrichsen/alpaca_2k_test
type: alpaca
dataset_prepared_path: last_run_prepared
val_set_size: 0
output_dir: ./outputs/lora-out
eval_sample_packing: false
adapter: lora
lora_model_dir:
sequence_len: 4096
sample_packing: true
lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
lora_target_modules:
- gate_proj
- down_proj
- up_proj
- q_proj
- v_proj
- k_proj
- o_proj
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 8
micro_batch_size: 1
num_epochs: 2
optimizer: adamw_torch_fused
lr_scheduler: cosine
learning_rate: 0.0002
bf16: auto
fp16: false
tf32: true
gradient_checkpointing: true
resume_from_checkpoint:
logging_steps: 1
flash_attention: false
sdp_attention: true
loss_watchdog_threshold: 5.0
loss_watchdog_patience: 3
warmup_steps: 10
evals_per_epoch: 4
saves_per_epoch: 1
weight_decay: 0.0
special_tokens:
# save_first_step: true # uncomment this to validate checkpoint saving works with your config