# OpenCLIP base model name
model_name: "ViT-L-14"
# Use these pretrained weights, provided by OpenCLIP
pretrained: "datacomp_xl_s13b_b90k"
compile: False
seed: 1337

device: "cuda"
# Output directory for finetuned lora weights and config. Will contain checkpoint folders with
# lora weights and config
output_dir: "/workload/bridge_output"

wandb: False
wandb_project: test-clipora

# Custom CSV dataset
train_dataset: "/workload/bridge_data/train.csv"
eval_dataset: "/workload/bridge_data/eval.csv"
datatype: "csv"
csv_separator: ","
image_col: "image_path"
text_col: "language_instruction"
shuffle: True
# How many workers to use in dataloader. Recommend using more than 1
workers: 8

lora_rank: 16
lora_alpha: 32
lora_dropout: 0.0

batch_size: 32
gradient_accumulation_steps: 1
gradient_checkpointing: False

use_8bit_adam: False

learning_rate: 1e-4
epochs: 3
warmup: 0.01
save_interval: 500
eval_interval: 30
eval_steps: 10
