Configuration Parsing
Warning:
In adapter_config.json: "peft.task_type" must be a string
ft-mit-b0-with-scene-parse-150-lora
This model is a fine-tuned version of nvidia/mit-b0 on the scene_parse_150 dataset. It achieves the following results on the evaluation set:
- Loss: 1.8279
- Mean Iou: 0.0003
- Mean Accuracy: 0.0004
- Overall Accuracy: 0.0038
- Accuracy Wall: nan
- Accuracy Building: 0.0205
- Accuracy Sky: 0.0
- Accuracy Floor: 0.0
- Accuracy Tree: 0.0
- Accuracy Ceiling: 0.0
- Accuracy Road: 0.0
- Accuracy Bed : 0.0005
- Accuracy Windowpane: 0.0
- Accuracy Grass: 0.0
- Accuracy Cabinet: 0.0
- Accuracy Sidewalk: 0.0
- Accuracy Person: 0.0
- Accuracy Earth: 0.0
- Accuracy Door: 0.0
- Accuracy Table: 0.0
- Accuracy Mountain: 0.0161
- 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: nan
- 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: nan
- Accuracy Desk: 0.0
- Accuracy Rock: 0.0
- Accuracy Wardrobe: 0.0
- Accuracy Lamp: 0.0
- Accuracy Bathtub: 0.0
- Accuracy Railing: nan
- 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: 0.0
- Accuracy Fireplace: 0.0
- Accuracy Refrigerator: nan
- Accuracy Grandstand: nan
- Accuracy Path: 0.0
- Accuracy Stairs: 0.0
- Accuracy Runway: 0.0
- Accuracy Case: 0.0
- Accuracy Pool table: nan
- Accuracy Pillow: nan
- Accuracy Screen door: 0.0
- Accuracy Stairway: 0.0
- Accuracy River: nan
- Accuracy Bridge: nan
- 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: nan
- Accuracy Computer: nan
- Accuracy Swivel chair: nan
- Accuracy Boat: nan
- Accuracy Bar: nan
- Accuracy Arcade machine: nan
- Accuracy Hovel: 0.0
- Accuracy Bus: 0.0
- Accuracy Towel: 0.0
- Accuracy Light: 0.0
- Accuracy Truck: 0.0
- Accuracy Tower: 0.0
- Accuracy Chandelier: nan
- Accuracy Awning: 0.0
- Accuracy Streetlight: nan
- Accuracy Booth: 0.0
- Accuracy Television receiver: 0.0
- Accuracy Airplane: nan
- Accuracy Dirt track: 0.0
- Accuracy Apparel: 0.0
- Accuracy Pole: 0.0
- Accuracy Land: nan
- Accuracy Bannister: nan
- Accuracy Escalator: nan
- Accuracy Ottoman: 0.0
- Accuracy Bottle: nan
- Accuracy Buffet: 0.0
- Accuracy Poster: 0.0
- Accuracy Stage: 0.0
- Accuracy Van: nan
- Accuracy Ship: nan
- Accuracy Fountain: 0.0
- Accuracy Conveyer belt: 0.0
- Accuracy Canopy: nan
- Accuracy Washer: nan
- Accuracy Plaything: nan
- Accuracy Swimming pool: 0.0
- Accuracy Stool: nan
- Accuracy Barrel: 0.0
- Accuracy Basket: nan
- Accuracy Waterfall: nan
- Accuracy Tent: 0.0
- Accuracy Bag: nan
- Accuracy Minibike: 0.0
- Accuracy Cradle: nan
- Accuracy Oven: nan
- Accuracy Ball: nan
- Accuracy Food: nan
- Accuracy Step: nan
- Accuracy Tank: 0.0
- Accuracy Trade name: 0.0
- Accuracy Microwave: 0.0
- Accuracy Pot: nan
- Accuracy Animal: nan
- Accuracy Bicycle: nan
- Accuracy Lake: nan
- Accuracy Dishwasher: nan
- Accuracy Screen: 0.0
- Accuracy Blanket: 0.0
- Accuracy Sculpture: 0.0
- Accuracy Hood: 0.0
- Accuracy Sconce: 0.0
- Accuracy Vase: nan
- Accuracy Traffic light: 0.0
- Accuracy Tray: nan
- Accuracy Ashcan: 0.0
- Accuracy Fan: nan
- Accuracy Pier: nan
- Accuracy Crt screen: 0.0
- Accuracy Plate: nan
- Accuracy Monitor: nan
- Accuracy Bulletin board: 0.0
- Accuracy Shower: nan
- Accuracy Radiator: nan
- Accuracy Glass: nan
- Accuracy Clock: 0.0
- Accuracy Flag: nan
- Iou Wall: 0.0
- Iou Building: 0.0129
- Iou Sky: 0.0
- Iou Floor: 0.0
- Iou Tree: 0.0
- Iou Ceiling: 0.0
- Iou Road: 0.0
- Iou Bed : 0.0002
- Iou Windowpane: 0.0
- Iou Grass: 0.0
- Iou Cabinet: 0.0
- Iou Sidewalk: 0.0
- Iou Person: 0.0
- Iou Earth: 0.0
- Iou Door: 0.0
- Iou Table: 0.0
- Iou Mountain: 0.0121
- 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: nan
- Iou Desk: 0.0
- Iou Rock: 0.0
- Iou Wardrobe: 0.0
- Iou Lamp: 0.0
- Iou Bathtub: 0.0
- Iou Railing: nan
- 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: 0.0
- Iou Fireplace: 0.0
- Iou Refrigerator: nan
- Iou Grandstand: nan
- Iou Path: 0.0
- Iou Stairs: 0.0
- Iou Runway: 0.0
- Iou Case: 0.0
- Iou Pool table: nan
- Iou Pillow: nan
- Iou Screen door: 0.0
- Iou Stairway: 0.0
- Iou River: nan
- Iou Bridge: nan
- 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: nan
- Iou Computer: nan
- Iou Swivel chair: nan
- Iou Boat: nan
- Iou Bar: nan
- Iou Arcade machine: nan
- Iou Hovel: 0.0
- Iou Bus: 0.0
- Iou Towel: 0.0
- Iou Light: 0.0
- Iou Truck: 0.0
- Iou Tower: 0.0
- Iou Chandelier: nan
- Iou Awning: 0.0
- Iou Streetlight: nan
- Iou Booth: 0.0
- Iou Television receiver: 0.0
- Iou Airplane: nan
- Iou Dirt track: 0.0
- Iou Apparel: 0.0
- Iou Pole: 0.0
- Iou Land: nan
- Iou Bannister: nan
- Iou Escalator: nan
- Iou Ottoman: 0.0
- Iou Bottle: nan
- Iou Buffet: 0.0
- Iou Poster: 0.0
- Iou Stage: 0.0
- Iou Van: nan
- Iou Ship: nan
- Iou Fountain: 0.0
- Iou Conveyer belt: 0.0
- Iou Canopy: nan
- Iou Washer: nan
- Iou Plaything: nan
- Iou Swimming pool: 0.0
- Iou Stool: nan
- Iou Barrel: 0.0
- Iou Basket: nan
- Iou Waterfall: nan
- Iou Tent: 0.0
- Iou Bag: nan
- Iou Minibike: 0.0
- Iou Cradle: nan
- Iou Oven: nan
- Iou Ball: nan
- Iou Food: nan
- Iou Step: nan
- Iou Tank: 0.0
- Iou Trade name: 0.0
- Iou Microwave: 0.0
- Iou Pot: nan
- Iou Animal: nan
- Iou Bicycle: nan
- Iou Lake: nan
- Iou Dishwasher: nan
- Iou Screen: 0.0
- Iou Blanket: 0.0
- Iou Sculpture: 0.0
- Iou Hood: 0.0
- Iou Sconce: 0.0
- Iou Vase: nan
- Iou Traffic light: 0.0
- Iou Tray: nan
- Iou Ashcan: 0.0
- Iou Fan: nan
- Iou Pier: nan
- Iou Crt screen: 0.0
- Iou Plate: nan
- Iou Monitor: nan
- Iou Bulletin board: 0.0
- Iou Shower: nan
- Iou Radiator: nan
- 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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
3.2136 | 1.0 | 29 | 2.6069 | 0.0001 | 0.0003 | 0.0045 | nan | 0.0263 | 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 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 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 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | nan | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | 0.0 | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | nan | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | 0.0128 | 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 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 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 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | nan | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | 0.0 | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | nan | 0.0 | nan | nan | nan | 0.0 | nan |
2.4379 | 2.0 | 58 | 2.0882 | 0.0001 | 0.0002 | 0.0024 | nan | 0.0139 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0003 | 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 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 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 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | nan | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | 0.0 | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | nan | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | 0.0094 | 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 | nan | 0.0 | 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 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | nan | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | 0.0 | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | nan | 0.0 | nan | nan | nan | 0.0 | nan |
2.0889 | 3.0 | 87 | 1.8879 | 0.0001 | 0.0002 | 0.0030 | nan | 0.0170 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0004 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0029 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 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 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | nan | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | 0.0 | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | nan | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | 0.0101 | 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 | 0.0025 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 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 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | nan | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | 0.0 | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | nan | 0.0 | nan | nan | nan | 0.0 | nan |
1.965 | 4.0 | 116 | 1.8387 | 0.0002 | 0.0003 | 0.0034 | nan | 0.0184 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0006 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0128 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 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 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | nan | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | 0.0 | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | nan | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | 0.0116 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0003 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0101 | 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 | nan | 0.0 | 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 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | nan | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | 0.0 | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | nan | 0.0 | nan | nan | nan | 0.0 | nan |
1.8371 | 5.0 | 145 | 1.8279 | 0.0003 | 0.0004 | 0.0038 | nan | 0.0205 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0005 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0161 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 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 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | nan | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | 0.0 | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | nan | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | 0.0129 | 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 | 0.0121 | 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 | nan | 0.0 | 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 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | nan | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | nan | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | 0.0 | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | nan | nan | 0.0 | nan | nan | nan | 0.0 | nan |
Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0
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Model tree for aisuko/ft-mit-b0-with-scene-parse-150-lora
Base model
nvidia/mit-b0