Training in progress, step 500

.gitignore

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+checkpoint-*/

config.json

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+{
+  "_name_or_path": "hustvl/yolos-tiny",
+  "architectures": [
+    "YolosForObjectDetection"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "auxiliary_loss": false,
+  "bbox_cost": 5,
+  "bbox_loss_coefficient": 5,
+  "class_cost": 1,
+  "eos_coefficient": 0.1,
+  "giou_cost": 2,
+  "giou_loss_coefficient": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 192,
+  "id2label": {
+    "0": "brain-tumor",
+    "1": "label0",
+    "2": "label1",
+    "3": "label2"
+  },
+  "image_size": [
+    800,
+    1333
+  ],
+  "initializer_range": 0.02,
+  "intermediate_size": 768,
+  "label2id": {
+    "brain-tumor": 0,
+    "label0": 1,
+    "label1": 2,
+    "label2": 3
+  },
+  "layer_norm_eps": 1e-12,
+  "model_type": "yolos",
+  "num_attention_heads": 3,
+  "num_channels": 3,
+  "num_detection_tokens": 100,
+  "num_hidden_layers": 12,
+  "patch_size": 16,
+  "qkv_bias": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.31.0",
+  "use_mid_position_embeddings": false
+}

preprocessor_config.json

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+{
+  "do_normalize": true,
+  "do_pad": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "format": "coco_detection",
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "YolosImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "longest_edge": 1333,
+    "shortest_edge": 512
+  }
+}

pytorch_model.bin

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