qa data exp

scripts/short_ctx/gemma_fw_qa_level_0.sh

@@ -0,0 +1,34 @@
+#!/bin/bash
+#SBATCH --job-name=ctxlora
+#SBATCH --nodes=1
+#SBATCH --partition=sakura-gpu
+#SBATCH --gpus=4
+#SBATCH --output=slurm_logs/%x-%j.out
+#SBATCH --error=slurm_logs/%x-%j.out
+
+uv run accelerate launch --num_processes=4 --gradient_accumulation_steps=2 --gradient_clipping=1.0 \
+--gpu_ids all --main_process_port 29562 intx_sft.py configs/fw_qa_v2_level_0.yaml \
+--model_name_or_path=google/gemma-2-2b-it \
+--num_train_epochs=5 \
+--per_device_train_batch_size=-1 \
+--gradient_accumulation_steps=2 \
+--per_device_eval_batch_size=64 \
+--target_modules=down_proj \
+--num_self_attends_per_block=8 \
+--num_latent_factor=1 \
+--num_pre_head_layers=1 \
+--lora_r=8 \
+--eval_steps=1000 \
+--save_steps=1000 \
+--learning_rate=4e-5 \
+--lora_dropout=0.0 \
+--neftune_noise_alpha=5 \
+--add_negative_prompt=False \
+--add_repeat_prompt=False \
+--use_sequence_packing=True \
+--max_packed_inp_len=16000 \
+--max_packed_ctx_len=32000 \
+--per_rank_gen=True \
+--per_layer_processing=True \
+--gen_lora_l1_reg_coef=0.1 \
+--logging_steps=50

scripts/short_ctx/gemma_fw_qa_level_0_tiny.sh

@@ -8,7 +8,7 @@
 
 uv run accelerate launch --num_processes=4 --gradient_accumulation_steps=2 --gradient_clipping=1.0 \
 --gpu_ids all --main_process_port 29562 intx_sft.py configs/fw_qa_v2_level_0_tiny.yaml \
---model_name_or_path=google/gemma-3-1b-it \
+--model_name_or_path=google/gemma-2-2b-it \
 --num_train_epochs=5 \
 --per_device_train_batch_size=-1 \
 --gradient_accumulation_steps=2 \

scripts/short_ctx/gemma_fw_qa_level_1.sh

@@ -0,0 +1,34 @@
+#!/bin/bash
+#SBATCH --job-name=ctxlora
+#SBATCH --nodes=1
+#SBATCH --partition=sakura-gpu
+#SBATCH --gpus=4
+#SBATCH --output=slurm_logs/%x-%j.out
+#SBATCH --error=slurm_logs/%x-%j.out
+
+uv run accelerate launch --num_processes=4 --gradient_accumulation_steps=2 --gradient_clipping=1.0 \
+--gpu_ids all --main_process_port 29563 intx_sft.py configs/fw_qa_v2_level_1.yaml \
+--model_name_or_path=google/gemma-2-2b-it \
+--num_train_epochs=5 \
+--per_device_train_batch_size=-1 \
+--gradient_accumulation_steps=2 \
+--per_device_eval_batch_size=64 \
+--target_modules=down_proj \
+--num_self_attends_per_block=8 \
+--num_latent_factor=1 \
+--num_pre_head_layers=1 \
+--lora_r=8 \
+--eval_steps=1000 \
+--save_steps=1000 \
+--learning_rate=4e-5 \
+--lora_dropout=0.0 \
+--neftune_noise_alpha=5 \
+--add_negative_prompt=False \
+--add_repeat_prompt=False \
+--use_sequence_packing=True \
+--max_packed_inp_len=16000 \
+--max_packed_ctx_len=32000 \
+--per_rank_gen=True \
+--per_layer_processing=True \
+--gen_lora_l1_reg_coef=0.1 \
+--logging_steps=50

scripts/short_ctx/gemma_fw_qa_level_2.sh

@@ -0,0 +1,34 @@
+#!/bin/bash
+#SBATCH --job-name=ctxlora
+#SBATCH --nodes=1
+#SBATCH --partition=sakura-gpu
+#SBATCH --gpus=4
+#SBATCH --output=slurm_logs/%x-%j.out
+#SBATCH --error=slurm_logs/%x-%j.out
+
+uv run accelerate launch --num_processes=4 --gradient_accumulation_steps=2 --gradient_clipping=1.0 \
+--gpu_ids all --main_process_port 29564 intx_sft.py configs/fw_qa_v2_level_2.yaml \
+--model_name_or_path=google/gemma-2-2b-it \
+--num_train_epochs=5 \
+--per_device_train_batch_size=-1 \
+--gradient_accumulation_steps=2 \
+--per_device_eval_batch_size=64 \
+--target_modules=down_proj \
+--num_self_attends_per_block=8 \
+--num_latent_factor=1 \
+--num_pre_head_layers=1 \
+--lora_r=8 \
+--eval_steps=1000 \
+--save_steps=1000 \
+--learning_rate=4e-5 \
+--lora_dropout=0.0 \
+--neftune_noise_alpha=5 \
+--add_negative_prompt=False \
+--add_repeat_prompt=False \
+--use_sequence_packing=True \
+--max_packed_inp_len=16000 \
+--max_packed_ctx_len=32000 \
+--per_rank_gen=True \
+--per_layer_processing=True \
+--gen_lora_l1_reg_coef=0.1 \
+--logging_steps=50

scripts/short_ctx/gemma_fw_qa_level_3.sh

@@ -7,8 +7,8 @@
 #SBATCH --error=slurm_logs/%x-%j.out
 
 uv run accelerate launch --num_processes=4 --gradient_accumulation_steps=2 --gradient_clipping=1.0 \
---gpu_ids all --main_process_port 29564 intx_sft.py configs/fw_qa_v2_level_3.yaml \
---model_name_or_path=google/gemma-3-1b-it \
+--gpu_ids all --main_process_port 29565 intx_sft.py configs/fw_qa_v2_level_3.yaml \
+--model_name_or_path=google/gemma-2-2b-it \
 --num_train_epochs=5 \
 --per_device_train_batch_size=-1 \
 --gradient_accumulation_steps=2 \

scripts/short_ctx/gemma_fw_qa_level_3_tiny.sh

@@ -8,7 +8,7 @@
 
 uv run accelerate launch --num_processes=4 --gradient_accumulation_steps=2 --gradient_clipping=1.0 \
 --gpu_ids all --main_process_port 29563 intx_sft.py configs/fw_qa_v2_level_3_tiny.yaml \
---model_name_or_path=google/gemma-3-1b-it \
+--model_name_or_path=google/gemma-2-2b-it \
 --num_train_epochs=5 \
 --per_device_train_batch_size=-1 \
 --gradient_accumulation_steps=2 \

scripts/short_ctx/gemma_squad.sh

@@ -8,7 +8,7 @@
 
 uv run accelerate launch --num_processes=4 --gradient_accumulation_steps=2 --gradient_clipping=1.0 \
 --gpu_ids all --main_process_port 29561 intx_sft.py configs/squad.yaml \
---model_name_or_path=google/gemma-3-1b-it \
+--model_name_or_path=google/gemma-2-2b-it \
 --num_train_epochs=5 \
 --per_device_train_batch_size=-1 \
 --gradient_accumulation_steps=2 \

scripts/short_ctx/gemma_squad_and_fw_qa_level_3.sh

@@ -7,8 +7,8 @@
 #SBATCH --error=slurm_logs/%x-%j.out
 
 uv run accelerate launch --num_processes=4 --gradient_accumulation_steps=2 --gradient_clipping=1.0 \
---gpu_ids all --main_process_port 29565 intx_sft.py configs/squad.yaml \
---model_name_or_path=google/gemma-3-1b-it \
+--gpu_ids all --main_process_port 29566 intx_sft.py configs/squad_fw_qa_v2_level_3.yaml \
+--model_name_or_path=google/gemma-2-2b-it \
 --num_train_epochs=5 \
 --per_device_train_batch_size=-1 \
 --gradient_accumulation_steps=2 \