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config.yaml

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+BASE_REPO_ID: google/paligemma-3b-pt-448
+FINETUNED_MODEL_ID: lovodkin93/paligemma-3b-pt-448_lora_mmnt_TV_concat_vertical-tgt-bottom-black_balanced
+OUTPUT_DIR_PATH: /home/slobodkin/reference_vnli/train_ref_vnli_autorater/models/paligemma-3b-pt-448/lora_mmnt_TV_concat_vertical-tgt-bottom-black_balanced
+INSTRUCTIONS: "You are presented with two images and a caption. The caption containes\
+  \ markups (<u> and </u>) around a mention of some {{ENTITY}}, whose image is the\
+  \ BOTTOM one. Your goal is to determine if the TOP image aligns with the caption,\
+  \ and also if it matches the {{ENTITY}} in the BOTTOM image within the caption's\
+  \ context. Your output should be '3' if the TOP image aligns with both the caption\
+  \ and the BOTTOM image, '2' if it only aligns with the caption, '1' if it only aligns\
+  \ with the BOTTOM image, and '0' if it aligns with neither.\n Caption: "
+ENTITY_INSTRUCTION_PLACEHOLDER: '{{ENTITY}}'
+DEBUG: false
+RESUME_FROM_CHECKPOINT: false
+MAX_LENGTH: 300
+CONCAT_REF_TGT_IMAGES: true
+CONCAT_IMAGES_TYPE: vertical-tgt-bottom-black
+TRAIN_PARAMS:
+  BALANCE_TRAIN_DATASETS: true
+  BATCH_SIZE: 4
+  FULL_FINETUNE: false
+  FINETUNE_LLM: true
+  FINETUNE_MM_PROJECTOR: false
+  FINETUNE_VISION_MODEL: false
+  GRADIENT_ACCUMULATION_STEPS: 2
+  EVAL_INTERVAL: 200
+  SAVE_INTERVAL: 200
+  SAVE_TOTAL_LIMIT: 20
+  METRIC_FOR_BEST_MODEL: Eval/accuracy
+DATA:
+  MEMENTOS:
+    IMG_DIR: /home/slobodkin/reference_vnli/datasets/mementos/images
+    DATASETS_CSV_BASE_DIR: /home/slobodkin/reference_vnli/train_ref_vnli_autorater/data/mementos/multiclass
+    VERSION: 03Nov2024
+    TRAIN:
+      DATASETS:
+      - name: train_min_balanced_multi_classification
+        task: mementos
+    EVAL:
+      DATASETS:
+      - name: dev_2000_instances
+        task: mementos
+  TVQA:
+    DATASETS_CSV_BASE_DIR: /home/slobodkin/reference_vnli/train_ref_vnli_autorater/data/TVQA_plus
+    VERSION: 15Dec2024
+    TRAIN:
+      DATASETS:
+      - name: train_balanced_full_200000_instances
+        task: TVQA
+    EVAL:
+      DATASETS:
+      - name: val_balanced_full_2000_instances
+        task: TVQA