doc-to-lora/configs/qa_short_ctx_compact.yaml
2025-07-21 09:03:58 +00:00

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YAML

output_dir: "" # just a placeholder
bf16: true
model_name_or_path: google/gemma-3-1b-it
label_names: ["labels"]
# eval_on_start: True
# eval_strategy: "steps"
# eval_steps: 500
# save_strategy: "no"
# # save_steps: 500
# logging_strategy: "steps"
# logging_steps: 100
# use_liger_kernel: true
# remove_unused_columns: false
# needed to avoid OOM by compute the metrics batch by batch
# w/o this the trainer stores logits of all sample in memory...
# batch_eval_metrics: true
per_device_train_batch_size: 8
per_device_eval_batch_size: 8
max_val_samples_per_ds: 1000
# optim: schedule_free_adamw
learning_rate: 0.00004
# lr_scheduler_type: "constant_with_warmup"
neftune_noise_alpha: 1
weight_decay: 0.01
warmup_steps: 100
dataloader_prefetch_factor: 16
dataloader_num_workers: 8
# LoRA
lora_r: 8
lora_dropout: 0.0
target_modules:
- down_proj
# short ctx data
train_ds_names:
- fw_qa_v2_2k_len_level_3
- squad_compact
- pwc_compact
- drop_compact
- ropes_compact
# the contexts are kinda long-ish
# - narrativeqa
# - quoref
# - synthetic_convqa
val_ds_names:
- fw_qa_v2_2k_len_level_0
- squad
- drop
- ropes
- pwc