Doc-to-LoRA release

scripts/main_exp/2-train-chunk.sh

@@ -0,0 +1,30 @@
+#!/bin/bash
+
+port=29051
+
+uv run accelerate launch --config_file accelerate_config.yaml --main_process_port $port \
+--num_processes=8 --gpu_ids all train.py \
+configs/main_exp/self_gen_lv1_closed_qa_1_l2l.yaml \
+--model_name_or_path=google/gemma-2-2b-it \
+--target_modules=down_proj \
+--lora_r=8 \
+--eval_strategy=no \
+--max_qas_len=512 \
+--max_qas_per_sample=1 \
+--per_rank_gen=True \
+--per_layer_processing=True \
+--gen_lora_l1_reg_coef=0.1 \
+--max_steps=20000 \
+--gradient_accumulation_steps=16 \
+--max_packed_inp_len=1024 \
+--max_packed_ctx_len=2048 \
+--use_per_ctx_average_loss=True \
+--use_kl_loss=True \
+--quantize_ctx_encoder=True \
+--torch_empty_cache_steps=10 \
+--from_pretrained_checkpoint=train_outputs/runs/$RUN_NAME/checkpoint-80000/pytorch_model.bin \
+--max_ctx_chunk_len=512 \
+--min_ctx_chunk_len=25 \
+--num_chunk_probs='{"1":"0.5", "2":"0.125", "3":"0.0625", "4":"0.0625", "5":"0.0625", "6":"0.0625", "7":"0.0625", "8":"0.0625"}' \
+--warmup_steps=2000 \
+--learning_rate=2e-5