segformer-b0-finetuned-Eduardo-food103-GOOGLE100
This model is a fine-tuned version of nvidia/mit-b0 on the EduardoPacheco/FoodSeg103 dataset. It achieves the following results on the evaluation set:
- Loss: 2.0865
- Mean Iou: 0.0515
- Mean Accuracy: 0.1257
- Overall Accuracy: 0.2045
- Accuracy Background: nan
- Accuracy Candy: nan
- Accuracy Egg tart: nan
- Accuracy French fries: 0.0
- Accuracy Chocolate: nan
- Accuracy Biscuit: nan
- Accuracy Popcorn: nan
- Accuracy Pudding: nan
- Accuracy Ice cream: 0.0
- Accuracy Cheese butter: 0.0
- Accuracy Cake: 0.0
- Accuracy Wine: 0.0
- Accuracy Milkshake: nan
- Accuracy Coffee: nan
- Accuracy Juice: 0.0
- Accuracy Milk: nan
- Accuracy Tea: nan
- Accuracy Almond: nan
- Accuracy Red beans: nan
- Accuracy Cashew: nan
- Accuracy Dried cranberries: nan
- Accuracy Soy: nan
- Accuracy Walnut: nan
- Accuracy Peanut: nan
- Accuracy Egg: nan
- Accuracy Apple: nan
- Accuracy Date: nan
- Accuracy Apricot: nan
- Accuracy Avocado: nan
- Accuracy Banana: nan
- Accuracy Strawberry: nan
- Accuracy Cherry: nan
- Accuracy Blueberry: nan
- Accuracy Raspberry: nan
- Accuracy Mango: nan
- Accuracy Olives: nan
- Accuracy Peach: 0.0
- Accuracy Lemon: nan
- Accuracy Pear: nan
- Accuracy Fig: nan
- Accuracy Pineapple: nan
- Accuracy Grape: nan
- Accuracy Kiwi: nan
- Accuracy Melon: nan
- Accuracy Orange: 0.0
- Accuracy Watermelon: nan
- Accuracy Steak: 0.8548
- Accuracy Pork: 0.5362
- Accuracy Chicken duck: 0.3458
- Accuracy Sausage: 0.0
- Accuracy Fried meat: nan
- Accuracy Lamb: 0.0
- Accuracy Sauce: 0.0
- Accuracy Crab: nan
- Accuracy Fish: nan
- Accuracy Shellfish: 0.0
- Accuracy Shrimp: 0.0
- Accuracy Soup: 0.0
- Accuracy Bread: 0.0157
- Accuracy Corn: 0.0
- Accuracy Hamburg: nan
- Accuracy Pizza: nan
- Accuracy hanamaki baozi: 0.0
- Accuracy Wonton dumplings: nan
- Accuracy Pasta: nan
- Accuracy Noodles: 0.2191
- Accuracy Rice: 0.3396
- Accuracy Pie: 0.0
- Accuracy Tofu: 0.0
- Accuracy Eggplant: nan
- Accuracy Potato: 0.6707
- Accuracy Garlic: nan
- Accuracy Cauliflower: 0.0
- Accuracy Tomato: 0.0295
- Accuracy Kelp: nan
- Accuracy Seaweed: nan
- Accuracy Spring onion: 0.0
- Accuracy Rape: 0.0
- Accuracy Ginger: nan
- Accuracy Okra: 0.0
- Accuracy Lettuce: 0.0014
- Accuracy Pumpkin: nan
- Accuracy Cucumber: 0.2728
- Accuracy White radish: 0.0
- Accuracy Carrot: 0.9345
- Accuracy Asparagus: nan
- Accuracy Bamboo shoots: nan
- Accuracy Broccoli: 0.7618
- Accuracy Celery stick: 0.0400
- Accuracy Cilantro mint: 0.0
- Accuracy Snow peas: nan
- Accuracy cabbage: nan
- Accuracy Bean sprouts: nan
- Accuracy Onion: 0.0075
- Accuracy Pepper: nan
- Accuracy Green beans: nan
- Accuracy French beans: nan
- Accuracy King oyster mushroom: nan
- Accuracy Shiitake: nan
- Accuracy Enoki mushroom: nan
- Accuracy Oyster mushroom: nan
- Accuracy White button mushroom: 0.0
- Accuracy Salad: nan
- Accuracy Other ingredients: 0.0
- Iou Background: 0.0
- Iou Candy: nan
- Iou Egg tart: nan
- Iou French fries: 0.0
- Iou Chocolate: nan
- Iou Biscuit: 0.0
- Iou Popcorn: nan
- Iou Pudding: nan
- Iou Ice cream: 0.0
- Iou Cheese butter: 0.0
- Iou Cake: 0.0
- Iou Wine: 0.0
- Iou Milkshake: nan
- Iou Coffee: nan
- Iou Juice: 0.0
- Iou Milk: nan
- Iou Tea: nan
- Iou Almond: nan
- Iou Red beans: nan
- Iou Cashew: nan
- Iou Dried cranberries: nan
- Iou Soy: nan
- Iou Walnut: nan
- Iou Peanut: nan
- Iou Egg: nan
- Iou Apple: nan
- Iou Date: nan
- Iou Apricot: nan
- Iou Avocado: nan
- Iou Banana: nan
- Iou Strawberry: nan
- Iou Cherry: nan
- Iou Blueberry: nan
- Iou Raspberry: nan
- Iou Mango: nan
- Iou Olives: nan
- Iou Peach: 0.0
- Iou Lemon: nan
- Iou Pear: nan
- Iou Fig: nan
- Iou Pineapple: nan
- Iou Grape: nan
- Iou Kiwi: nan
- Iou Melon: nan
- Iou Orange: 0.0
- Iou Watermelon: nan
- Iou Steak: 0.1109
- Iou Pork: 0.2326
- Iou Chicken duck: 0.1176
- Iou Sausage: 0.0
- Iou Fried meat: nan
- Iou Lamb: 0.0
- Iou Sauce: 0.0
- Iou Crab: nan
- Iou Fish: nan
- Iou Shellfish: 0.0
- Iou Shrimp: 0.0
- Iou Soup: 0.0
- Iou Bread: 0.0065
- Iou Corn: 0.0
- Iou Hamburg: nan
- Iou Pizza: nan
- Iou hanamaki baozi: 0.0
- Iou Wonton dumplings: nan
- Iou Pasta: nan
- Iou Noodles: 0.1944
- Iou Rice: 0.2630
- Iou Pie: 0.0
- Iou Tofu: 0.0
- Iou Eggplant: nan
- Iou Potato: 0.2078
- Iou Garlic: nan
- Iou Cauliflower: 0.0
- Iou Tomato: 0.0283
- Iou Kelp: nan
- Iou Seaweed: nan
- Iou Spring onion: 0.0
- Iou Rape: 0.0
- Iou Ginger: nan
- Iou Okra: 0.0
- Iou Lettuce: 0.0010
- Iou Pumpkin: nan
- Iou Cucumber: 0.1036
- Iou White radish: 0.0
- Iou Carrot: 0.4668
- Iou Asparagus: nan
- Iou Bamboo shoots: nan
- Iou Broccoli: 0.3830
- Iou Celery stick: 0.0400
- Iou Cilantro mint: 0.0
- Iou Snow peas: nan
- Iou cabbage: nan
- Iou Bean sprouts: nan
- Iou Onion: 0.0073
- Iou Pepper: nan
- Iou Green beans: nan
- Iou French beans: nan
- Iou King oyster mushroom: nan
- Iou Shiitake: nan
- Iou Enoki mushroom: nan
- Iou Oyster mushroom: nan
- Iou White button mushroom: 0.0
- Iou Salad: nan
- Iou Other ingredients: 0.0
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: 0.0001
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Candy | Accuracy Egg tart | Accuracy French fries | Accuracy Chocolate | Accuracy Biscuit | Accuracy Popcorn | Accuracy Pudding | Accuracy Ice cream | Accuracy Cheese butter | Accuracy Cake | Accuracy Wine | Accuracy Milkshake | Accuracy Coffee | Accuracy Juice | Accuracy Milk | Accuracy Tea | Accuracy Almond | Accuracy Red beans | Accuracy Cashew | Accuracy Dried cranberries | Accuracy Soy | Accuracy Walnut | Accuracy Peanut | Accuracy Egg | Accuracy Apple | Accuracy Date | Accuracy Apricot | Accuracy Avocado | Accuracy Banana | Accuracy Strawberry | Accuracy Cherry | Accuracy Blueberry | Accuracy Raspberry | Accuracy Mango | Accuracy Olives | Accuracy Peach | Accuracy Lemon | Accuracy Pear | Accuracy Fig | Accuracy Pineapple | Accuracy Grape | Accuracy Kiwi | Accuracy Melon | Accuracy Orange | Accuracy Watermelon | Accuracy Steak | Accuracy Pork | Accuracy Chicken duck | Accuracy Sausage | Accuracy Fried meat | Accuracy Lamb | Accuracy Sauce | Accuracy Crab | Accuracy Fish | Accuracy Shellfish | Accuracy Shrimp | Accuracy Soup | Accuracy Bread | Accuracy Corn | Accuracy Hamburg | Accuracy Pizza | Accuracy hanamaki baozi | Accuracy Wonton dumplings | Accuracy Pasta | Accuracy Noodles | Accuracy Rice | Accuracy Pie | Accuracy Tofu | Accuracy Eggplant | Accuracy Potato | Accuracy Garlic | Accuracy Cauliflower | Accuracy Tomato | Accuracy Kelp | Accuracy Seaweed | Accuracy Spring onion | Accuracy Rape | Accuracy Ginger | Accuracy Okra | Accuracy Lettuce | Accuracy Pumpkin | Accuracy Cucumber | Accuracy White radish | Accuracy Carrot | Accuracy Asparagus | Accuracy Bamboo shoots | Accuracy Broccoli | Accuracy Celery stick | Accuracy Cilantro mint | Accuracy Snow peas | Accuracy cabbage | Accuracy Bean sprouts | Accuracy Onion | Accuracy Pepper | Accuracy Green beans | Accuracy French beans | Accuracy King oyster mushroom | Accuracy Shiitake | Accuracy Enoki mushroom | Accuracy Oyster mushroom | Accuracy White button mushroom | Accuracy Salad | Accuracy Other ingredients | Iou Background | Iou Candy | Iou Egg tart | Iou French fries | Iou Chocolate | Iou Biscuit | Iou Popcorn | Iou Pudding | Iou Ice cream | Iou Cheese butter | Iou Cake | Iou Wine | Iou Milkshake | Iou Coffee | Iou Juice | Iou Milk | Iou Tea | Iou Almond | Iou Red beans | Iou Cashew | Iou Dried cranberries | Iou Soy | Iou Walnut | Iou Peanut | Iou Egg | Iou Apple | Iou Date | Iou Apricot | Iou Avocado | Iou Banana | Iou Strawberry | Iou Cherry | Iou Blueberry | Iou Raspberry | Iou Mango | Iou Olives | Iou Peach | Iou Lemon | Iou Pear | Iou Fig | Iou Pineapple | Iou Grape | Iou Kiwi | Iou Melon | Iou Orange | Iou Watermelon | Iou Steak | Iou Pork | Iou Chicken duck | Iou Sausage | Iou Fried meat | Iou Lamb | Iou Sauce | Iou Crab | Iou Fish | Iou Shellfish | Iou Shrimp | Iou Soup | Iou Bread | Iou Corn | Iou Hamburg | Iou Pizza | Iou hanamaki baozi | Iou Wonton dumplings | Iou Pasta | Iou Noodles | Iou Rice | Iou Pie | Iou Tofu | Iou Eggplant | Iou Potato | Iou Garlic | Iou Cauliflower | Iou Tomato | Iou Kelp | Iou Seaweed | Iou Spring onion | Iou Rape | Iou Ginger | Iou Okra | Iou Lettuce | Iou Pumpkin | Iou Cucumber | Iou White radish | Iou Carrot | Iou Asparagus | Iou Bamboo shoots | Iou Broccoli | Iou Celery stick | Iou Cilantro mint | Iou Snow peas | Iou cabbage | Iou Bean sprouts | Iou Onion | Iou Pepper | Iou Green beans | Iou French beans | Iou King oyster mushroom | Iou Shiitake | Iou Enoki mushroom | Iou Oyster mushroom | Iou White button mushroom | Iou Salad | Iou Other ingredients |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2.7669 | 14.2857 | 100 | 2.5982 | 0.0437 | 0.1131 | 0.1847 | nan | nan | nan | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0.0 | nan | nan | nan | nan | nan | nan | nan | 0.0 | nan | 0.9470 | 0.0774 | 0.0606 | 0.0 | nan | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0843 | 0.0 | nan | nan | 0.0 | nan | nan | 0.0 | 0.6846 | 0.0 | 0.0 | nan | 0.5680 | nan | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | 0.0 | 0.0 | nan | 0.3424 | 0.0 | 0.9617 | nan | nan | 0.7870 | 0.0112 | 0.0003 | nan | nan | nan | 0.0 | nan | nan | nan | nan | nan | nan | nan | 0.0 | nan | 0.0 | 0.0 | nan | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0.0 | nan | nan | nan | nan | nan | nan | nan | 0.0 | nan | 0.0730 | 0.0747 | 0.0481 | 0.0 | nan | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0302 | 0.0 | nan | nan | 0.0 | nan | nan | 0.0 | 0.6074 | 0.0 | 0.0 | nan | 0.2870 | nan | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | nan | 0.0 | 0.0 | nan | 0.0955 | 0.0 | 0.3976 | nan | nan | 0.2527 | 0.0110 | 0.0003 | nan | nan | nan | 0.0 | nan | 0.0 | nan | nan | nan | nan | nan | 0.0 | nan | 0.0 |
| 1.8931 | 28.5714 | 200 | 2.2174 | 0.0416 | 0.1085 | 0.1951 | nan | nan | nan | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0.0 | nan | nan | nan | nan | nan | nan | nan | 0.0 | nan | 0.4517 | 0.5716 | 0.0521 | 0.0 | nan | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0020 | 0.0 | nan | nan | 0.0 | nan | nan | 0.1063 | 0.2845 | 0.0 | 0.0 | nan | 0.8817 | nan | 0.0 | 0.0162 | nan | nan | 0.0 | 0.0 | nan | 0.0 | 0.0074 | nan | 0.2246 | 0.0 | 0.9538 | nan | nan | 0.7794 | 0.0013 | 0.0037 | nan | nan | nan | 0.0026 | nan | nan | nan | nan | nan | nan | nan | 0.0 | nan | 0.0 | 0.0 | nan | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0.0 | nan | nan | nan | nan | nan | nan | nan | 0.0 | nan | 0.0589 | 0.2125 | 0.0357 | 0.0 | nan | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0009 | 0.0 | nan | nan | 0.0 | nan | nan | 0.1060 | 0.2194 | 0.0 | 0.0 | nan | 0.2077 | nan | 0.0 | 0.0159 | nan | nan | 0.0 | 0.0 | nan | 0.0 | 0.0059 | nan | 0.0737 | 0.0 | 0.4452 | nan | nan | 0.3571 | 0.0013 | 0.0036 | nan | nan | nan | 0.0025 | nan | nan | nan | nan | nan | nan | nan | 0.0 | nan | 0.0 |
| 1.5479 | 42.8571 | 300 | 2.0865 | 0.0515 | 0.1257 | 0.2045 | nan | nan | nan | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0.0 | nan | nan | nan | nan | nan | nan | nan | 0.0 | nan | 0.8548 | 0.5362 | 0.3458 | 0.0 | nan | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0157 | 0.0 | nan | nan | 0.0 | nan | nan | 0.2191 | 0.3396 | 0.0 | 0.0 | nan | 0.6707 | nan | 0.0 | 0.0295 | nan | nan | 0.0 | 0.0 | nan | 0.0 | 0.0014 | nan | 0.2728 | 0.0 | 0.9345 | nan | nan | 0.7618 | 0.0400 | 0.0 | nan | nan | nan | 0.0075 | nan | nan | nan | nan | nan | nan | nan | 0.0 | nan | 0.0 | 0.0 | nan | nan | 0.0 | nan | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0.0 | nan | nan | nan | nan | nan | nan | nan | 0.0 | nan | 0.1109 | 0.2326 | 0.1176 | 0.0 | nan | 0.0 | 0.0 | nan | nan | 0.0 | 0.0 | 0.0 | 0.0065 | 0.0 | nan | nan | 0.0 | nan | nan | 0.1944 | 0.2630 | 0.0 | 0.0 | nan | 0.2078 | nan | 0.0 | 0.0283 | nan | nan | 0.0 | 0.0 | nan | 0.0 | 0.0010 | nan | 0.1036 | 0.0 | 0.4668 | nan | nan | 0.3830 | 0.0400 | 0.0 | nan | nan | nan | 0.0073 | nan | nan | nan | nan | nan | nan | nan | 0.0 | nan | 0.0 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3
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Model tree for sumeyya/segformer-b0-finetuned-Eduardo-food103-GOOGLE100
Base model
nvidia/mit-b0