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Description
I am trying to recreate the StarCoder2-Instruct-v0.1 model; however, the model produced by the provided command in the README (copied below) does not match the evaluation of the StarCoder2-Instruct-v0.1 model on HF.
I actually see quite a bit of discrepancy between the two models' evaluations: humaneval on your HF version is 7 points higher than on my reproduced model (both models were evaluated locally by me in the same environment).
MODEL_KEY=bigcode/starcoder2-15b
LR=1e-5
EPOCH=4
SEQ_LEN=1280
WARMUP_RATIO=0.05
OUTPUT_DIR=/path/to/output_model
DATASET_FILE=/path/to/50k-dataset.jsonl
accelerate launch -m star_align.train \
--model_key $MODEL_KEY \
--model_name_or_path $MODEL_KEY \
--use_flash_attention True \
--datafile_paths $DATASET_FILE \
--output_dir $OUTPUT_DIR \
--bf16 True \
--num_train_epochs $EPOCH \
--max_training_seq_length $SEQ_LEN \
--pad_to_max_length False \
--per_device_train_batch_size 1 \
--gradient_accumulation_steps 64 \
--group_by_length False \
--ddp_find_unused_parameters False \
--logging_steps 1 \
--log_level info \
--optim adafactor \
--max_grad_norm -1 \
--warmup_ratio $WARMUP_RATIO \
--learning_rate $LR \
--lr_scheduler_type linearAre the parameters in the README correct for the released model? Are you adding anything in your accelerate config? i.e. any model wrappers or something else?
For the data, I just ran:
>>> from datasets import load_dataset
>>> load_dataset("bigcode/self-oss-instruct-sc2-exec-filter-50k", split="train").to_json("/path/to/50k-dataset.jsonl", lines=True)Do you have any ideas on how I can reproduce your model? Thanks!