End of training

README.md

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+---
+license: other
+base_model: nvidia/mit-b0
+tags:
+- vision
+- image-segmentation
+- generated_from_trainer
+model-index:
+- name: segformer-b0-finetuned
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# segformer-b0-finetuned
+
+This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the segments/sidewalk-semantic dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5754
+- Mean Iou: 0.2781
+- Mean Accuracy: 0.3329
+- Overall Accuracy: 0.8463
+- Per Category Iou: [0.0, 0.7432161129630078, 0.854265404236928, 0.4606401052721709, 0.6557337899613191, 0.4079867997829282, nan, 0.37471812939221005, 0.2905341043386837, 0.0, 0.7537587486511262, 0.0, 0.0, nan, 0.0, 0.019848656872972055, 0.0, 0.0, 0.7115931639469374, nan, 0.3661808713379434, 0.13378413732653244, 0.0, nan, 0.0, 0.23570903658727577, 0.0, 0.0, 0.8461792428096935, 0.7553019453875489, 0.9045825383881589, 0.0, 0.0, 0.10651182264386322, 0.0]
+- Per Category Accuracy: [0.0, 0.8511274737458464, 0.9523527728262475, 0.7305783824446481, 0.7179823443918317, 0.5112934364530293, nan, 0.4671955914617317, 0.39620749876026823, 0.0, 0.9325380267720194, 0.0, 0.0, nan, 0.0, 0.019920987025907694, 0.0, 0.0, 0.9114075726560573, nan, 0.4767221960460328, 0.14080931640440494, 0.0, nan, 0.0, 0.2902864462270403, 0.0, 0.0, 0.9417630123717813, 0.8946072183599384, 0.9626510283976625, 0.0, 0.0, 0.12104456389804058, 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: 5e-05
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Per Category Iou                                                                                                                                                                                                                                                                                                                                                                                                                                       | Per Category Accuracy                                                                                                                                                                                                                                                                                                                                                                                                                                |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
+| 0.6702        | 1.0   | 400  | 0.7027          | 0.2195   | 0.2629        | 0.8084           | [0.0, 0.6792133271879363, 0.7849474176188894, 0.058328120930117175, 0.6300690246185523, 0.25673461142351706, nan, 0.3004378389548008, 0.0, 0.0, 0.6990982425959871, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.6732565754528083, nan, 0.2872208279956378, 0.00018886917594771138, 0.0, nan, 0.0, 0.04832964515878562, 0.0, 0.0, 0.8103176781510323, 0.6868793807107686, 0.8837386972387465, 0.0, 0.0, 0.005328297121957592, 0.0]                             | [0.0, 0.766565968404771, 0.9690642801889813, 0.05881921997258986, 0.6774284161746986, 0.2997799346472589, nan, 0.3604784648706302, 0.0, 0.0, 0.9238506174053699, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.879793151515724, nan, 0.3814629549547224, 0.0001889329509116015, 0.0, nan, 0.0, 0.049252727470549255, 0.0, 0.0, 0.92204060605898, 0.9165746690826654, 0.9399161153753854, 0.0, 0.0, 0.005432287151031732, 0.0]                                 |
+| 0.3787        | 2.0   | 800  | 0.6242          | 0.2529   | 0.3048        | 0.8336           | [0.0, 0.7200155470846057, 0.8500725277201905, 0.4283923004744409, 0.6393695507210657, 0.35502977816991826, nan, 0.35184539253673836, 0.007092160389449536, 0.0, 0.7043921336269122, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.6907551328541987, nan, 0.30912243068319983, 0.08139332433133045, 0.0, nan, 0.0, 0.188100947571913, 0.0, 0.0, 0.8385996121617959, 0.7447284921504436, 0.8944303097872178, 0.0, 0.0, 0.03573598106370054, 0.0]                  | [0.0, 0.8883665924421738, 0.9304929976181545, 0.6379432034836245, 0.684408431327974, 0.47546406343261166, nan, 0.46904807570859863, 0.007098812013540027, 0.0, 0.9393400531924911, 0.0, 0.0, nan, 0.0, 0.0, 0.0, 0.0, 0.9030339520321862, nan, 0.38990531390988364, 0.08456558485802895, 0.0, nan, 0.0, 0.22015360876747014, 0.0, 0.0, 0.9441960488646456, 0.8731757915405423, 0.9605664489132197, 0.0, 0.0, 0.0402316629096584, 0.0]                |
+| 0.5272        | 3.0   | 1200 | 0.5910          | 0.2640   | 0.3116        | 0.8409           | [0.0, 0.7417372358583919, 0.8491040334276788, 0.5026923409983705, 0.6531274799797995, 0.39671746797276214, nan, 0.3489393985838212, 0.10917691003765771, 0.0, 0.7340253134142348, 0.0, 0.0, nan, 0.0, 0.0015906711475390872, 0.0, 0.0, 0.6888929372303201, nan, 0.3000933215998536, 0.09430463167198322, 0.0, nan, 0.0, 0.22079460109263602, 0.0, 0.0, 0.8375430585634192, 0.7432674869295846, 0.8979452744557967, 0.0, 0.0, 0.06465850622764936, 0.0] | [0.0, 0.8742236634719254, 0.9469015516965127, 0.6845976124235456, 0.7153136135405865, 0.4838119970613863, nan, 0.426013369696913, 0.11595265302602359, 0.0, 0.9307602006332041, 0.0, 0.0, nan, 0.0, 0.0015906711475390872, 0.0, 0.0, 0.9211760279107508, nan, 0.3640489760089845, 0.09822101537391639, 0.0, nan, 0.0, 0.27522724799952525, 0.0, 0.0, 0.9529837430876597, 0.8328291532204077, 0.9626684254773068, 0.0, 0.0, 0.07271163516559737, 0.0] |
+| 1.0028        | 4.0   | 1600 | 0.5819          | 0.2749   | 0.3265        | 0.8451           | [0.0, 0.7442319582171808, 0.8549546101758252, 0.4558465282708946, 0.6592549345415454, 0.40147520263994, nan, 0.3560786579426865, 0.2724675418610539, 0.0, 0.7615078761694535, 0.0, 0.0, nan, 0.0, 0.01480792989181263, 0.0, 0.0, 0.6971675525618446, nan, 0.3289306001269004, 0.1400376526683254, 0.0, nan, 0.0, 0.2330975509072671, 0.0, 0.0, 0.8412274001878343, 0.7610379911113287, 0.9042555512089849, 0.0, 0.0, 0.09514392306437187, 0.0]         | [0.0, 0.8831147123698461, 0.9454704608007805, 0.7031575260834061, 0.7194367374187804, 0.4940337653992012, nan, 0.4313144685568867, 0.3654837110023501, 0.0, 0.911745245214873, 0.0, 0.0, nan, 0.0, 0.01483662361250094, 0.0, 0.0, 0.9249937012782616, nan, 0.39416005628239303, 0.1487585698177601, 0.0, nan, 0.0, 0.28903522220353906, 0.0, 0.0, 0.9446123320713813, 0.8885032163816529, 0.9544933330809051, 0.0, 0.0, 0.10758314548292006, 0.0]    |
+| 1.3105        | 5.0   | 2000 | 0.5754          | 0.2781   | 0.3329        | 0.8463           | [0.0, 0.7432161129630078, 0.854265404236928, 0.4606401052721709, 0.6557337899613191, 0.4079867997829282, nan, 0.37471812939221005, 0.2905341043386837, 0.0, 0.7537587486511262, 0.0, 0.0, nan, 0.0, 0.019848656872972055, 0.0, 0.0, 0.7115931639469374, nan, 0.3661808713379434, 0.13378413732653244, 0.0, nan, 0.0, 0.23570903658727577, 0.0, 0.0, 0.8461792428096935, 0.7553019453875489, 0.9045825383881589, 0.0, 0.0, 0.10651182264386322, 0.0]    | [0.0, 0.8511274737458464, 0.9523527728262475, 0.7305783824446481, 0.7179823443918317, 0.5112934364530293, nan, 0.4671955914617317, 0.39620749876026823, 0.0, 0.9325380267720194, 0.0, 0.0, nan, 0.0, 0.019920987025907694, 0.0, 0.0, 0.9114075726560573, nan, 0.4767221960460328, 0.14080931640440494, 0.0, nan, 0.0, 0.2902864462270403, 0.0, 0.0, 0.9417630123717813, 0.8946072183599384, 0.9626510283976625, 0.0, 0.0, 0.12104456389804058, 0.0]  |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

config.json

@@ -0,0 +1,144 @@
+{
+  "_name_or_path": "nvidia/mit-b0",
+  "architectures": [
+    "SegformerForSemanticSegmentation"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "classifier_dropout_prob": 0.1,
+  "decoder_hidden_size": 256,
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsampling_rates": [
+    1,
+    4,
+    8,
+    16
+  ],
+  "drop_path_rate": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_sizes": [
+    32,
+    64,
+    160,
+    256
+  ],
+  "id2label": {
+    "0": "unlabeled",
+    "1": "flat-road",
+    "2": "flat-sidewalk",
+    "3": "flat-crosswalk",
+    "4": "flat-cyclinglane",
+    "5": "flat-parkingdriveway",
+    "6": "flat-railtrack",
+    "7": "flat-curb",
+    "8": "human-person",
+    "9": "human-rider",
+    "10": "vehicle-car",
+    "11": "vehicle-truck",
+    "12": "vehicle-bus",
+    "13": "vehicle-tramtrain",
+    "14": "vehicle-motorcycle",
+    "15": "vehicle-bicycle",
+    "16": "vehicle-caravan",
+    "17": "vehicle-cartrailer",
+    "18": "construction-building",
+    "19": "construction-door",
+    "20": "construction-wall",
+    "21": "construction-fenceguardrail",
+    "22": "construction-bridge",
+    "23": "construction-tunnel",
+    "24": "construction-stairs",
+    "25": "object-pole",
+    "26": "object-trafficsign",
+    "27": "object-trafficlight",
+    "28": "nature-vegetation",
+    "29": "nature-terrain",
+    "30": "sky",
+    "31": "void-ground",
+    "32": "void-dynamic",
+    "33": "void-static",
+    "34": "void-unclear"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "construction-bridge": 22,
+    "construction-building": 18,
+    "construction-door": 19,
+    "construction-fenceguardrail": 21,
+    "construction-stairs": 24,
+    "construction-tunnel": 23,
+    "construction-wall": 20,
+    "flat-crosswalk": 3,
+    "flat-curb": 7,
+    "flat-cyclinglane": 4,
+    "flat-parkingdriveway": 5,
+    "flat-railtrack": 6,
+    "flat-road": 1,
+    "flat-sidewalk": 2,
+    "human-person": 8,
+    "human-rider": 9,
+    "nature-terrain": 29,
+    "nature-vegetation": 28,
+    "object-pole": 25,
+    "object-trafficlight": 27,
+    "object-trafficsign": 26,
+    "sky": 30,
+    "unlabeled": 0,
+    "vehicle-bicycle": 15,
+    "vehicle-bus": 12,
+    "vehicle-car": 10,
+    "vehicle-caravan": 16,
+    "vehicle-cartrailer": 17,
+    "vehicle-motorcycle": 14,
+    "vehicle-tramtrain": 13,
+    "vehicle-truck": 11,
+    "void-dynamic": 32,
+    "void-ground": 31,
+    "void-static": 33,
+    "void-unclear": 34
+  },
+  "layer_norm_eps": 1e-06,
+  "mlp_ratios": [
+    4,
+    4,
+    4,
+    4
+  ],
+  "model_type": "segformer",
+  "num_attention_heads": [
+    1,
+    2,
+    5,
+    8
+  ],
+  "num_channels": 3,
+  "num_encoder_blocks": 4,
+  "patch_sizes": [
+    7,
+    3,
+    3,
+    3
+  ],
+  "reshape_last_stage": true,
+  "semantic_loss_ignore_index": 255,
+  "sr_ratios": [
+    8,
+    4,
+    2,
+    1
+  ],
+  "strides": [
+    4,
+    2,
+    2,
+    2
+  ],
+  "torch_dtype": "float32",
+  "transformers_version": "4.38.2"
+}

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