Create sft.slurm

sft.slurm

@@ -0,0 +1,39 @@
+#!/bin/bash
+#SBATCH --job-name=apigen-fine-tune
+#SBATCH --partition=hopper-prod
+#SBATCH --qos=normal
+#SBATCH --nodes=1
+#SBATCH --ntasks-per-node=1
+#SBATCH --gpus-per-node=8
+#SBATCH --output=./logs/%x-%j.out
+#SBATCH --err=./logs/%x-%j.err
+#SBATCH --time=02-00:00:00
+
+set -ex
+
+module load cuda/12.1
+
+source .venv/bin/activate
+
+srun --nodes=1 --ntasks=1 --export=ALL,ACCELERATE_LOG_LEVEL=info accelerate launch --config_file examples/accelerate_configs/deepspeed_zero3.yaml examples/scripts/sft.py \
+    --run_name=Llama-3.2-1B-Instruct-APIGen-FC-v0.1 \
+    --model_name_or_path="meta-llama/Llama-3.2-1B-Instruct" \
+    --dataset_name="plaguss/apigen-synth-trl" \
+    --report_to="wandb" \
+    --learning_rate=5.0e-06 \
+    --lr_scheduler_type="cosine" \
+    --per_device_train_batch_size=6 \
+    --per_device_eval_batch_size=6 \
+    --do_eval \
+    --eval_strategy="steps" \
+    --gradient_accumulation_steps=2 \
+    --output_dir="data/Llama-3.2-1B-Instruct-APIGen-FC-v0.1" \
+    --logging_steps=5 \
+    --eval_steps=50 \
+    --num_train_epochs=2 \
+    --max_steps=-1 \
+    --warmup_steps=50 \
+    --max_seq_length=2048 \
+    --push_to_hub \
+    --gradient_checkpointing \
+    --bf16