--- license: other base_model: nvidia/mit-b0 tags: - generated_from_trainer datasets: - scene_parse_150 library_name: peft model-index: - name: ft-mit-b0-with-scene-parse-150-lora results: [] --- # ft-mit-b0-with-scene-parse-150-lora This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the scene_parse_150 dataset. It achieves the following results on the evaluation set: - Loss: 2.2760 - Mean Iou: 0.0001 - Mean Accuracy: 0.0003 - Overall Accuracy: 0.0028 - Accuracy Wall: nan - Accuracy Building: 0.0252 - Accuracy Sky: 0.0 - Accuracy Floor: 0.0 - Accuracy Tree: 0.0 - Accuracy Ceiling: 0.0 - Accuracy Road: 0.0 - Accuracy Bed : 0.0008 - Accuracy Windowpane: 0.0 - Accuracy Grass: 0.0 - Accuracy Cabinet: 0.0 - Accuracy Sidewalk: 0.0007 - Accuracy Person: 0.0 - Accuracy Earth: 0.0 - Accuracy Door: 0.0 - Accuracy Table: 0.0 - Accuracy Mountain: 0.0 - Accuracy Plant: 0.0 - Accuracy Curtain: 0.0 - Accuracy Chair: 0.0 - Accuracy Car: 0.0 - Accuracy Water: 0.0 - Accuracy Painting: 0.0 - Accuracy Sofa: 0.0 - Accuracy Shelf: 0.0 - Accuracy House: nan - Accuracy Sea: 0.0 - Accuracy Mirror: 0.0 - Accuracy Rug: 0.0 - Accuracy Field: 0.0 - Accuracy Armchair: 0.0 - Accuracy Seat: 0.0 - Accuracy Fence: 0.0 - Accuracy Desk: 0.0 - Accuracy Rock: nan - Accuracy Wardrobe: 0.0 - Accuracy Lamp: 0.0 - Accuracy Bathtub: 0.0 - Accuracy Railing: 0.0 - Accuracy Cushion: 0.0 - Accuracy Base: 0.0 - Accuracy Box: 0.0 - Accuracy Column: 0.0 - Accuracy Signboard: 0.0 - Accuracy Chest of drawers: 0.0 - Accuracy Counter: nan - Accuracy Sand: 0.0 - Accuracy Sink: nan - Accuracy Skyscraper: nan - Accuracy Fireplace: 0.0 - Accuracy Refrigerator: 0.0 - Accuracy Grandstand: 0.0 - Accuracy Path: 0.0 - Accuracy Stairs: nan - Accuracy Runway: nan - Accuracy Case: 0.0 - Accuracy Pool table: 0.0 - Accuracy Pillow: 0.0 - Accuracy Screen door: 0.0 - Accuracy Stairway: nan - Accuracy River: 0.0 - Accuracy Bridge: 0.0 - Accuracy Bookcase: nan - Accuracy Blind: 0.0 - Accuracy Coffee table: 0.0 - Accuracy Toilet: 0.0 - Accuracy Flower: 0.0 - Accuracy Book: 0.0 - Accuracy Hill: 0.0 - Accuracy Bench: 0.0 - Accuracy Countertop: 0.0 - Accuracy Stove: nan - Accuracy Palm: nan - Accuracy Kitchen island: 0.0 - Accuracy Computer: nan - Accuracy Swivel chair: nan - Accuracy Boat: nan - Accuracy Bar: 0.0 - Accuracy Arcade machine: nan - Accuracy Hovel: 0.0 - Accuracy Bus: 0.0 - Accuracy Towel: 0.0 - Accuracy Light: 0.0 - Accuracy Truck: nan - Accuracy Tower: nan - Accuracy Chandelier: 0.0 - Accuracy Awning: 0.0 - Accuracy Streetlight: nan - Accuracy Booth: 0.0 - Accuracy Television receiver: nan - Accuracy Airplane: nan - Accuracy Dirt track: nan - Accuracy Apparel: 0.0 - Accuracy Pole: nan - Accuracy Land: nan - Accuracy Bannister: nan - Accuracy Escalator: nan - Accuracy Ottoman: 0.0 - Accuracy Bottle: nan - Accuracy Buffet: nan - Accuracy Poster: 0.0 - Accuracy Stage: 0.0 - Accuracy Van: 0.0 - Accuracy Ship: nan - Accuracy Fountain: nan - Accuracy Conveyer belt: nan - Accuracy Canopy: 0.0 - Accuracy Washer: 0.0 - Accuracy Plaything: nan - Accuracy Swimming pool: 0.0 - Accuracy Stool: nan - Accuracy Barrel: nan - Accuracy Basket: 0.0 - Accuracy Waterfall: nan - Accuracy Tent: 0.0 - Accuracy Bag: nan - Accuracy Minibike: nan - Accuracy Cradle: 0.0 - Accuracy Oven: 0.0 - Accuracy Ball: 0.0 - Accuracy Food: nan - Accuracy Step: nan - Accuracy Tank: 0.0 - Accuracy Trade name: 0.0 - Accuracy Microwave: nan - Accuracy Pot: nan - Accuracy Animal: 0.0 - Accuracy Bicycle: nan - Accuracy Lake: 0.0 - Accuracy Dishwasher: 0.0 - Accuracy Screen: 0.0 - Accuracy Blanket: 0.0 - Accuracy Sculpture: nan - Accuracy Hood: 0.0 - Accuracy Sconce: 0.0 - Accuracy Vase: 0.0 - Accuracy Traffic light: 0.0 - Accuracy Tray: 0.0 - Accuracy Ashcan: 0.0 - Accuracy Fan: nan - Accuracy Pier: 0.0 - Accuracy Crt screen: nan - Accuracy Plate: nan - Accuracy Monitor: nan - Accuracy Bulletin board: nan - Accuracy Shower: nan - Accuracy Radiator: 0.0 - Accuracy Glass: nan - Accuracy Clock: 0.0 - Accuracy Flag: nan - Iou Wall: 0.0 - Iou Building: 0.0138 - Iou Sky: 0.0 - Iou Floor: 0.0 - Iou Tree: 0.0 - Iou Ceiling: 0.0 - Iou Road: 0.0 - Iou Bed : 0.0003 - Iou Windowpane: 0.0 - Iou Grass: 0.0 - Iou Cabinet: 0.0 - Iou Sidewalk: 0.0007 - Iou Person: 0.0 - Iou Earth: 0.0 - Iou Door: 0.0 - Iou Table: 0.0 - Iou Mountain: 0.0 - Iou Plant: 0.0 - Iou Curtain: 0.0 - Iou Chair: 0.0 - Iou Car: 0.0 - Iou Water: 0.0 - Iou Painting: 0.0 - Iou Sofa: 0.0 - Iou Shelf: 0.0 - Iou House: nan - Iou Sea: 0.0 - Iou Mirror: 0.0 - Iou Rug: 0.0 - Iou Field: 0.0 - Iou Armchair: 0.0 - Iou Seat: 0.0 - Iou Fence: 0.0 - Iou Desk: 0.0 - Iou Rock: nan - Iou Wardrobe: 0.0 - Iou Lamp: 0.0 - Iou Bathtub: 0.0 - Iou Railing: 0.0 - Iou Cushion: 0.0 - Iou Base: 0.0 - Iou Box: 0.0 - Iou Column: 0.0 - Iou Signboard: 0.0 - Iou Chest of drawers: 0.0 - Iou Counter: nan - Iou Sand: 0.0 - Iou Sink: nan - Iou Skyscraper: nan - Iou Fireplace: 0.0 - Iou Refrigerator: 0.0 - Iou Grandstand: 0.0 - Iou Path: 0.0 - Iou Stairs: nan - Iou Runway: nan - Iou Case: 0.0 - Iou Pool table: 0.0 - Iou Pillow: 0.0 - Iou Screen door: 0.0 - Iou Stairway: nan - Iou River: 0.0 - Iou Bridge: 0.0 - Iou Bookcase: nan - Iou Blind: 0.0 - Iou Coffee table: 0.0 - Iou Toilet: 0.0 - Iou Flower: 0.0 - Iou Book: 0.0 - Iou Hill: 0.0 - Iou Bench: 0.0 - Iou Countertop: 0.0 - Iou Stove: nan - Iou Palm: nan - Iou Kitchen island: 0.0 - Iou Computer: nan - Iou Swivel chair: nan - Iou Boat: nan - Iou Bar: 0.0 - Iou Arcade machine: nan - Iou Hovel: 0.0 - Iou Bus: 0.0 - Iou Towel: 0.0 - Iou Light: 0.0 - Iou Truck: nan - Iou Tower: nan - Iou Chandelier: 0.0 - Iou Awning: 0.0 - Iou Streetlight: nan - Iou Booth: 0.0 - Iou Television receiver: nan - Iou Airplane: nan - Iou Dirt track: nan - Iou Apparel: 0.0 - Iou Pole: nan - Iou Land: nan - Iou Bannister: nan - Iou Escalator: nan - Iou Ottoman: 0.0 - Iou Bottle: nan - Iou Buffet: nan - Iou Poster: 0.0 - Iou Stage: 0.0 - Iou Van: 0.0 - Iou Ship: nan - Iou Fountain: nan - Iou Conveyer belt: nan - Iou Canopy: 0.0 - Iou Washer: 0.0 - Iou Plaything: nan - Iou Swimming pool: 0.0 - Iou Stool: nan - Iou Barrel: nan - Iou Basket: 0.0 - Iou Waterfall: nan - Iou Tent: 0.0 - Iou Bag: nan - Iou Minibike: nan - Iou Cradle: 0.0 - Iou Oven: 0.0 - Iou Ball: 0.0 - Iou Food: nan - Iou Step: nan - Iou Tank: 0.0 - Iou Trade name: 0.0 - Iou Microwave: nan - Iou Pot: nan - Iou Animal: 0.0 - Iou Bicycle: nan - Iou Lake: 0.0 - Iou Dishwasher: 0.0 - Iou Screen: 0.0 - Iou Blanket: 0.0 - Iou Sculpture: nan - Iou Hood: 0.0 - Iou Sconce: 0.0 - Iou Vase: 0.0 - Iou Traffic light: 0.0 - Iou Tray: 0.0 - Iou Ashcan: 0.0 - Iou Fan: nan - Iou Pier: 0.0 - Iou Crt screen: nan - Iou Plate: nan - Iou Monitor: nan - Iou Bulletin board: nan - Iou Shower: nan - Iou Radiator: 0.0 - Iou Glass: nan - Iou Clock: 0.0 - Iou Flag: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0005 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Wall | Accuracy Building | Accuracy Sky | Accuracy Floor | Accuracy Tree | Accuracy Ceiling | Accuracy Road | Accuracy Bed | Accuracy Windowpane | Accuracy Grass | Accuracy Cabinet | Accuracy Sidewalk | Accuracy Person | Accuracy Earth | Accuracy Door | Accuracy Table | Accuracy Mountain | Accuracy Plant | Accuracy Curtain | Accuracy Chair | Accuracy Car | Accuracy Water | Accuracy Painting | Accuracy Sofa | Accuracy Shelf | Accuracy House | Accuracy Sea | Accuracy Mirror | Accuracy Rug | Accuracy Field | Accuracy Armchair | Accuracy Seat | Accuracy Fence | Accuracy Desk | Accuracy Rock | Accuracy Wardrobe | Accuracy Lamp | Accuracy Bathtub | Accuracy Railing | Accuracy Cushion | Accuracy Base | Accuracy Box | Accuracy Column | Accuracy Signboard | Accuracy Chest of drawers | Accuracy Counter | Accuracy Sand | Accuracy Sink | Accuracy Skyscraper | Accuracy Fireplace | Accuracy Refrigerator | Accuracy Grandstand | Accuracy Path | Accuracy Stairs | Accuracy Runway | Accuracy Case | Accuracy Pool table | Accuracy Pillow | Accuracy Screen door | Accuracy Stairway | Accuracy River | Accuracy Bridge | Accuracy Bookcase | Accuracy Blind | Accuracy Coffee table | Accuracy Toilet | Accuracy Flower | Accuracy Book | Accuracy Hill | Accuracy Bench | Accuracy Countertop | Accuracy Stove | Accuracy Palm | Accuracy Kitchen island | Accuracy Computer | Accuracy Swivel chair | Accuracy Boat | Accuracy Bar | Accuracy Arcade machine | Accuracy Hovel | Accuracy Bus | Accuracy Towel | Accuracy Light | Accuracy Truck | Accuracy Tower | Accuracy Chandelier | Accuracy Awning | Accuracy Streetlight | Accuracy Booth | Accuracy Television receiver | Accuracy Airplane | Accuracy Dirt track | Accuracy Apparel | Accuracy Pole | Accuracy Land | Accuracy Bannister | Accuracy Escalator | Accuracy Ottoman | Accuracy Bottle | Accuracy Buffet | Accuracy Poster | Accuracy Stage | Accuracy Van | Accuracy Ship | Accuracy Fountain | Accuracy Conveyer belt | Accuracy Canopy | Accuracy Washer | Accuracy Plaything | Accuracy Swimming pool | Accuracy Stool | Accuracy Barrel | Accuracy Basket | Accuracy Waterfall | Accuracy Tent | Accuracy Bag | Accuracy Minibike | Accuracy Cradle | Accuracy Oven | Accuracy Ball | Accuracy Food | Accuracy Step | Accuracy Tank | Accuracy Trade name | Accuracy Microwave | Accuracy Pot | Accuracy Animal | Accuracy Bicycle | Accuracy Lake | Accuracy Dishwasher | Accuracy Screen | Accuracy Blanket | Accuracy Sculpture | Accuracy Hood | Accuracy Sconce | Accuracy Vase | Accuracy Traffic light | Accuracy Tray | Accuracy Ashcan | Accuracy Fan | Accuracy Pier | Accuracy Crt screen | Accuracy Plate | Accuracy Monitor | Accuracy Bulletin board | Accuracy Shower | Accuracy Radiator | Accuracy Glass | Accuracy Clock | Accuracy Flag | Iou Wall | Iou Building | Iou Sky | Iou Floor | Iou Tree | Iou Ceiling | Iou Road | Iou Bed | Iou Windowpane | Iou Grass | Iou Cabinet | Iou Sidewalk | Iou Person | Iou Earth | Iou Door | Iou Table | Iou Mountain | Iou Plant | Iou Curtain | Iou Chair | Iou Car | Iou Water | Iou Painting | Iou Sofa | Iou Shelf | Iou House | Iou Sea | Iou Mirror | Iou Rug | Iou Field | Iou Armchair | Iou Seat | Iou Fence | Iou Desk | Iou Rock | Iou Wardrobe | Iou Lamp | Iou Bathtub | Iou Railing | Iou Cushion | Iou Base | Iou Box | Iou Column | Iou Signboard | Iou Chest of drawers | Iou Counter | Iou Sand | Iou Sink | Iou Skyscraper | Iou Fireplace | Iou Refrigerator | Iou Grandstand | Iou Path | Iou Stairs | Iou Runway | Iou Case | Iou Pool table | Iou Pillow | Iou Screen door | Iou Stairway | Iou River | Iou Bridge | Iou Bookcase | Iou Blind | Iou Coffee table | Iou Toilet | Iou Flower | Iou Book | Iou Hill | Iou Bench | Iou Countertop | Iou Stove | Iou Palm | Iou Kitchen island | Iou Computer | Iou Swivel chair | Iou Boat | Iou Bar | Iou Arcade machine | Iou Hovel | Iou Bus | Iou Towel | Iou Light | Iou Truck | Iou Tower | Iou Chandelier | Iou Awning | Iou Streetlight | Iou Booth | Iou Television receiver | Iou Airplane | Iou Dirt track | Iou Apparel | Iou Pole | Iou Land | Iou Bannister | Iou Escalator | Iou Ottoman | Iou Bottle | Iou Buffet | Iou Poster | Iou Stage | Iou Van | Iou Ship | Iou Fountain | Iou Conveyer belt | Iou Canopy | Iou Washer | Iou Plaything | Iou Swimming pool | Iou Stool | Iou Barrel | Iou Basket | Iou Waterfall | Iou Tent | Iou Bag | Iou Minibike | Iou Cradle | Iou Oven | Iou Ball | Iou Food | Iou Step | Iou Tank | Iou Trade name | Iou Microwave | Iou Pot | Iou Animal | Iou Bicycle | Iou Lake | Iou Dishwasher | Iou Screen | Iou Blanket | Iou Sculpture | Iou Hood | Iou Sconce | Iou Vase | Iou Traffic light | Iou Tray | Iou Ashcan | Iou Fan | Iou Pier | Iou Crt screen | Iou Plate | Iou Monitor | Iou Bulletin board | Iou Shower | Iou Radiator | Iou Glass | Iou Clock | Iou Flag | 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| 3.0768 | 1.0 | 29 | 3.0142 | 0.0003 | 0.0006 | 0.0063 | nan | 0.0578 | 0.0 | 0.0018 | 0.0 | 0.0 | 0.0 | 0.0001 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | 0.0 | nan | nan | nan | 0.0 | nan | nan | nan | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | 0.0 | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | nan | nan | nan | nan | 0.0 | nan | 0.0 | nan | 0.0 | 0.0288 | 0.0 | 0.0002 | 0.0 | 0.0 | 0.0 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | 0.0 | nan | nan | nan | 0.0 | nan | nan | nan | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | 0.0 | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | nan | nan | nan | nan | 0.0 | nan | 0.0 | nan | | 2.3753 | 2.0 | 58 | 2.5389 | 0.0002 | 0.0003 | 0.0030 | nan | 0.0276 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0002 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | 0.0 | nan | nan | nan | 0.0 | nan | nan | nan | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | 0.0 | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | nan | nan | nan | nan | 0.0 | nan | 0.0 | nan | 0.0 | 0.0158 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0001 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | 0.0 | nan | nan | nan | 0.0 | nan | nan | nan | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | 0.0 | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | nan | nan | nan | nan | 0.0 | nan | 0.0 | nan | | 2.1067 | 3.0 | 87 | 2.3853 | 0.0002 | 0.0003 | 0.0028 | nan | 0.0254 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0009 | 0.0 | 0.0 | 0.0 | 0.0010 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | 0.0 | nan | nan | nan | 0.0 | nan | nan | nan | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | 0.0 | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | nan | nan | nan | nan | 0.0 | nan | 0.0 | nan | 0.0 | 0.0141 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0003 | 0.0 | 0.0 | 0.0 | 0.0010 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | 0.0 | nan | nan | nan | 0.0 | nan | nan | nan | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | 0.0 | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | nan | nan | nan | nan | 0.0 | nan | 0.0 | nan | | 1.9646 | 4.0 | 116 | 2.2850 | 0.0001 | 0.0002 | 0.0023 | nan | 0.0208 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0005 | 0.0 | 0.0 | 0.0 | 0.0007 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | 0.0 | nan | nan | nan | 0.0 | nan | nan | nan | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | 0.0 | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | nan | nan | nan | nan | 0.0 | nan | 0.0 | nan | 0.0 | 0.0118 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0002 | 0.0 | 0.0 | 0.0 | 0.0007 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | 0.0 | nan | nan | nan | 0.0 | nan | nan | nan | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | 0.0 | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | nan | nan | nan | nan | 0.0 | nan | 0.0 | nan | | 2.017 | 5.0 | 145 | 2.2760 | 0.0001 | 0.0003 | 0.0028 | nan | 0.0252 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0008 | 0.0 | 0.0 | 0.0 | 0.0007 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | 0.0 | nan | nan | nan | 0.0 | nan | nan | nan | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | 0.0 | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | nan | nan | nan | nan | 0.0 | nan | 0.0 | nan | 0.0 | 0.0138 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0003 | 0.0 | 0.0 | 0.0 | 0.0007 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | 0.0 | nan | nan | nan | 0.0 | nan | nan | nan | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | 0.0 | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | nan | nan | nan | nan | 0.0 | nan | 0.0 | nan | ### Framework versions - PEFT 0.7.1 - Transformers 4.36.2 - Pytorch 2.5.1+cu124 - Datasets 2.15.0 - Tokenizers 0.15.2