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# Copyright (c) 2022, salesforce.com, inc.
# All rights reserved.
# SPDX-License-Identifier: BSD-3-Clause
# For full license text, see the LICENSE file in the repo root or https://opensource.org/licenses/BSD-3-Clause
# Overall Accuracy is: 51.88 (result different from BLIP-2 paper due to different implementation and transformers version)
model:
arch: blip2_opt
model_type: pretrain_opt2.7b
use_grad_checkpoint: False
datasets:
coco_vqa: # name of the dataset builder
type: eval
vis_processor:
eval:
name: "blip_image_eval"
image_size: 224
text_processor:
eval:
name: "blip_question"
# build_info:
# images:
# storage: '/export/share/datasets/vision/coco/images/'
run:
task: vqa
# optimization-specific
batch_size_train: 16
batch_size_eval: 64
num_workers: 4
# inference-specific
max_len: 10
min_len: 1
num_beams: 5
inference_method: "generate"
prompt: "Question: {} Short answer:"
seed: 42
output_dir: "output/BLIP2/VQA"
evaluate: True
test_splits: ["val"]
# distribution-specific
device: "cuda"
world_size: 1
dist_url: "env://"
distributed: True
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