Upload unimernet_tiny.yaml
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models/MFR/unimernet_tiny/unimernet_tiny.yaml
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model:
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arch: unimernet
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model_type: unimernet
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model_config:
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model_name: ./models/unimernet_tiny
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max_seq_len: 1536
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load_pretrained: True
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pretrained: './models/unimernet_tiny/pytorch_model.pth'
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tokenizer_config:
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path: ./models/unimernet_tiny
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datasets:
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formula_rec_eval:
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vis_processor:
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eval:
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name: "formula_image_eval"
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image_size:
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- 192
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- 672
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run:
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runner: runner_iter
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task: unimernet_train
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batch_size_train: 64
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batch_size_eval: 64
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num_workers: 1
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iters_per_inner_epoch: 2000
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max_iters: 60000
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seed: 42
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output_dir: "../output/demo"
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evaluate: True
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test_splits: [ "eval" ]
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device: "cuda"
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world_size: 1
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dist_url: "env://"
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distributed: True
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distributed_type: ddp # or fsdp when train llm
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generate_cfg:
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temperature: 0.0
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