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End of training

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: dandelin/vilt-b32-mlm
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: test-model
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # test-model
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+
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+ This model is a fine-tuned version of [dandelin/vilt-b32-mlm](https://huggingface.co/dandelin/vilt-b32-mlm) on an unknown dataset.
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 20
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+
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+ ### Training results
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+
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.37.2
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+ - Pytorch 2.2.0
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.1
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+ {
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+ "_name_or_path": "dandelin/vilt-b32-mlm",
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+ "architectures": [
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+ "ViltForQuestionAnswering"
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+ ],
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+ "attention_probs_dropout_prob": 0.0,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.0,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "yes",
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+ "1": "black and white",
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+ "2": "sidewalk",
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+ "3": "full",
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+ "4": "lanyard",
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+ "5": "at table",
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+ "6": "security",
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+ "7": "canopy",
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+ "8": "plate",
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+ "9": "4",
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+ "10": "red",
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+ "11": "cloudy",
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+ "12": "down",
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+ "13": "large",
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+ "14": "jeep",
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+ "15": "dirt",
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+ "16": "monitor",
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+ "17": "crown",
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+ "18": "low",
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+ "19": "smile",
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+ "20": "don't know",
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+ "21": "park",
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+ "22": "necklace",
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+ "23": "8:35",
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+ "24": "2000",
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+ "25": "style",
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+ "26": "2013",
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+ "27": "8",
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+ "28": "clock",
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+ "30": "air",
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+ "31": "desert",
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+ "32": "skateboarding",
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+ "33": "skier",
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+ "34": "window",
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+ "35": "hat",
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+ "36": "white",
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+ "37": "donut",
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+ "38": "photographer",
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+ "39": "dog",
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+ "40": "shelter",
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+ "41": "not sure",
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+ "42": "red and blue",
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+ "45": "big ben",
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+ "50": "protection",
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+ "51": "bike rack",
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+ "52": "nothing",
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+ "53": "tent",
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+ "54": "plain",
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+ "55": "solid",
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+ "56": "bikes",
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+ "57": "2",
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+ "58": "smiling",
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+ "59": "white and black",
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+ "60": "brick",
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+ "61": "gray",
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+ "62": "snow",
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+ "63": "door",
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+ "64": "blue and white",
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+ "65": "picnic table",
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+ "66": "doughnut",
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+ "67": "outside",
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+ "68": "5",
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+ "69": "fence",
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+ "70": "arrow",
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+ "71": "camera",
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+ "72": "9:35",
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+ "73": "man",
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+ "74": "3",
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+ "75": "giraffes",
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+ "76": "1",
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+ "77": "birthday",
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+ "78": "ball",
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+ "79": "net",
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+ "80": "tv",
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+ "81": "trees",
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+ "82": "walking",
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+ "83": "7:45",
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+ "84": "blue",
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+ "85": "small",
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+ "86": "exit",
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+ "91": "human",
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+ "92": "beige",
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+ "93": "they aren't",
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+ "94": "natural",
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+ "95": "lady",
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+ "96": "roof",
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+ "97": "right",
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+ "98": "2010",
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+ "99": "happy",
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+ "100": "curtains",
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+ "102": "hair",
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+ "103": "lying down",
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+ "104": "table",
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+ "105": "wall",
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+ "106": "tabby",
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+ "107": "on street",
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+ "108": "bicycles",
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+ "109": "shade",
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+ "110": "6",
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+ "111": "stripes",
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+ "112": "soccer ball",
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+ "113": "king",
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+ "114": "white and blue",
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+ "115": "0",
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+ "116": "many",
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+ "117": "giraffe",
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+ "118": "ice cream",
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+ "119": "laying down",
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+ "120": "gray and black",
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+ "121": "skateboard",
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+ "122": "bricks",
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+ "123": "shrimp",
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+ "124": "cup",
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+ "125": "watching",
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+ "126": "forest",
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+ "127": "woods",
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+ "128": "beagle",
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+ "129": "yellow",
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+ "130": "street",
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+ "131": "stand",
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+ "132": "on road",
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+ "133": "french",
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+ "134": "shadow",
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+ "135": "snowboarding",
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+ "136": "queen",
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+ "137": "bedroom",
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+ "138": "talking on phone",
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+ "139": "black",
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+ "140": "car",
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+ "141": "plastic",
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+ "142": "cat",
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+ "145": "clear",
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+ size 4664
vocab.txt ADDED
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