End of training

README.md

@@ -0,0 +1,174 @@
+---
+license: apache-2.0
+base_model: microsoft/resnet-50
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: Dogs-Breed-Image-Classification-V0
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.7444120505344995
+---
+
+<!-- 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. -->
+
+# Dogs-Breed-Image-Classification-V0
+
+This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.8210
+- Accuracy: 0.7444
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 100
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 13.4902       | 1.0   | 515   | 4.7822          | 0.0104   |
+| 4.7159        | 2.0   | 1030  | 4.6822          | 0.0323   |
+| 4.6143        | 3.0   | 1545  | 4.5940          | 0.0554   |
+| 4.4855        | 4.0   | 2060  | 4.5027          | 0.0935   |
+| 4.36          | 5.0   | 2575  | 4.3961          | 0.1239   |
+| 4.2198        | 6.0   | 3090  | 4.3112          | 0.1528   |
+| 4.0882        | 7.0   | 3605  | 4.1669          | 0.1747   |
+| 3.9314        | 8.0   | 4120  | 4.0775          | 0.2021   |
+| 3.7863        | 9.0   | 4635  | 3.9487          | 0.2310   |
+| 3.6511        | 10.0  | 5150  | 3.9028          | 0.2466   |
+| 3.5168        | 11.0  | 5665  | 3.8635          | 0.2626   |
+| 3.3999        | 12.0  | 6180  | 3.7550          | 0.2767   |
+| 3.3037        | 13.0  | 6695  | 3.6973          | 0.2884   |
+| 3.1613        | 14.0  | 7210  | 3.6315          | 0.3037   |
+| 3.0754        | 15.0  | 7725  | 3.4839          | 0.3188   |
+| 2.9441        | 16.0  | 8240  | 3.4406          | 0.3302   |
+| 2.8579        | 17.0  | 8755  | 3.3528          | 0.3406   |
+| 2.7531        | 18.0  | 9270  | 3.3132          | 0.3472   |
+| 2.6477        | 19.0  | 9785  | 3.2736          | 0.3567   |
+| 2.5422        | 20.0  | 10300 | 3.1950          | 0.3756   |
+| 2.4629        | 21.0  | 10815 | 3.1174          | 0.4004   |
+| 2.3735        | 22.0  | 11330 | 2.9916          | 0.4225   |
+| 2.2436        | 23.0  | 11845 | 2.9205          | 0.4509   |
+| 2.1578        | 24.0  | 12360 | 2.9197          | 0.4689   |
+| 2.0671        | 25.0  | 12875 | 2.8196          | 0.4866   |
+| 1.9902        | 26.0  | 13390 | 2.7117          | 0.4961   |
+| 1.8737        | 27.0  | 13905 | 2.7129          | 0.5078   |
+| 1.7945        | 28.0  | 14420 | 2.6654          | 0.5143   |
+| 1.7092        | 29.0  | 14935 | 2.6273          | 0.5301   |
+| 1.6228        | 30.0  | 15450 | 2.5407          | 0.5454   |
+| 1.5744        | 31.0  | 15965 | 2.5412          | 0.5559   |
+| 1.4761        | 32.0  | 16480 | 2.4658          | 0.5658   |
+| 1.4084        | 33.0  | 16995 | 2.4247          | 0.5673   |
+| 1.2624        | 34.0  | 17510 | 2.3766          | 0.5758   |
+| 1.2066        | 35.0  | 18025 | 2.2879          | 0.5843   |
+| 1.124         | 36.0  | 18540 | 2.2039          | 0.5872   |
+| 1.074         | 37.0  | 19055 | 2.2469          | 0.5965   |
+| 0.9937        | 38.0  | 19570 | 2.1575          | 0.6011   |
+| 0.9418        | 39.0  | 20085 | 2.0854          | 0.6122   |
+| 0.8812        | 40.0  | 20600 | 1.9991          | 0.6254   |
+| 0.819         | 41.0  | 21115 | 2.0161          | 0.6312   |
+| 0.771         | 42.0  | 21630 | 1.9253          | 0.6375   |
+| 0.7128        | 43.0  | 22145 | 1.9412          | 0.6390   |
+| 0.6434        | 44.0  | 22660 | 1.8463          | 0.6509   |
+| 0.6138        | 45.0  | 23175 | 1.8163          | 0.6650   |
+| 0.5325        | 46.0  | 23690 | 1.7881          | 0.6710   |
+| 0.498         | 47.0  | 24205 | 1.7526          | 0.6744   |
+| 0.4565        | 48.0  | 24720 | 1.7155          | 0.6859   |
+| 0.4109        | 49.0  | 25235 | 1.6874          | 0.6946   |
+| 0.3681        | 50.0  | 25750 | 1.7386          | 0.6997   |
+| 0.3306        | 51.0  | 26265 | 1.6578          | 0.7104   |
+| 0.2913        | 52.0  | 26780 | 1.6641          | 0.7104   |
+| 0.2598        | 53.0  | 27295 | 1.6823          | 0.7162   |
+| 0.2311        | 54.0  | 27810 | 1.6835          | 0.7157   |
+| 0.2115        | 55.0  | 28325 | 1.6581          | 0.7206   |
+| 0.1843        | 56.0  | 28840 | 1.6286          | 0.7274   |
+| 0.1668        | 57.0  | 29355 | 1.6358          | 0.7225   |
+| 0.1483        | 58.0  | 29870 | 1.6422          | 0.7250   |
+| 0.132         | 59.0  | 30385 | 1.6618          | 0.7284   |
+| 0.1164        | 60.0  | 30900 | 1.6894          | 0.7262   |
+| 0.1043        | 61.0  | 31415 | 1.6923          | 0.7276   |
+| 0.0937        | 62.0  | 31930 | 1.6627          | 0.7323   |
+| 0.0826        | 63.0  | 32445 | 1.6280          | 0.7342   |
+| 0.0743        | 64.0  | 32960 | 1.6204          | 0.7366   |
+| 0.0638        | 65.0  | 33475 | 1.6890          | 0.7383   |
+| 0.0603        | 66.0  | 33990 | 1.6967          | 0.7335   |
+| 0.0491        | 67.0  | 34505 | 1.6975          | 0.7306   |
+| 0.0459        | 68.0  | 35020 | 1.7242          | 0.7337   |
+| 0.0416        | 69.0  | 35535 | 1.7019          | 0.7374   |
+| 0.0382        | 70.0  | 36050 | 1.7098          | 0.7381   |
+| 0.0378        | 71.0  | 36565 | 1.7188          | 0.7383   |
+| 0.0326        | 72.0  | 37080 | 1.8212          | 0.7376   |
+| 0.0323        | 73.0  | 37595 | 1.7965          | 0.7393   |
+| 0.0299        | 74.0  | 38110 | 1.7934          | 0.7301   |
+| 0.0259        | 75.0  | 38625 | 1.7799          | 0.7335   |
+| 0.0276        | 76.0  | 39140 | 1.8456          | 0.7301   |
+| 0.0257        | 77.0  | 39655 | 1.8551          | 0.7391   |
+| 0.0234        | 78.0  | 40170 | 1.7780          | 0.7391   |
+| 0.0222        | 79.0  | 40685 | 1.8216          | 0.7362   |
+| 0.0195        | 80.0  | 41200 | 1.8333          | 0.7352   |
+| 0.0214        | 81.0  | 41715 | 1.8526          | 0.7430   |
+| 0.0207        | 82.0  | 42230 | 1.8581          | 0.7364   |
+| 0.0171        | 83.0  | 42745 | 1.8329          | 0.7393   |
+| 0.0175        | 84.0  | 43260 | 1.8841          | 0.7396   |
+| 0.0165        | 85.0  | 43775 | 1.8381          | 0.7345   |
+| 0.0152        | 86.0  | 44290 | 1.8192          | 0.7379   |
+| 0.0168        | 87.0  | 44805 | 1.8538          | 0.7388   |
+| 0.0158        | 88.0  | 45320 | 1.8390          | 0.7371   |
+| 0.0181        | 89.0  | 45835 | 1.8555          | 0.7374   |
+| 0.0142        | 90.0  | 46350 | 1.7987          | 0.7352   |
+| 0.0147        | 91.0  | 46865 | 1.8446          | 0.7427   |
+| 0.0142        | 92.0  | 47380 | 1.8210          | 0.7444   |
+| 0.0124        | 93.0  | 47895 | 1.8233          | 0.7405   |
+| 0.0128        | 94.0  | 48410 | 1.8517          | 0.7393   |
+| 0.0135        | 95.0  | 48925 | 1.8408          | 0.7413   |
+| 0.0122        | 96.0  | 49440 | 1.8153          | 0.7396   |
+| 0.0141        | 97.0  | 49955 | 1.8645          | 0.7432   |
+| 0.0121        | 98.0  | 50470 | 1.8526          | 0.7430   |
+| 0.0124        | 99.0  | 50985 | 1.8693          | 0.7388   |
+| 0.0113        | 100.0 | 51500 | 1.8051          | 0.7427   |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.3.0
+- Datasets 2.15.0
+- Tokenizers 0.15.1

config.json

@@ -0,0 +1,285 @@
+{
+  "_name_or_path": "microsoft/resnet-50",
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "Afghan_hound",
+    "1": "African_hunting_dog",
+    "10": "Border_terrier",
+    "100": "kuvasz",
+    "101": "malamute",
+    "102": "malinois",
+    "103": "miniature_pinscher",
+    "104": "miniature_poodle",
+    "105": "miniature_schnauzer",
+    "106": "otterhound",
+    "107": "papillon",
+    "108": "pug",
+    "109": "redbone",
+    "11": "Boston_bull",
+    "110": "schipperke",
+    "111": "silky_terrier",
+    "112": "soft",
+    "113": "standard_poodle",
+    "114": "standard_schnauzer",
+    "115": "toy_poodle",
+    "116": "toy_terrier",
+    "117": "vizsla",
+    "118": "whippet",
+    "119": "wire",
+    "12": "Bouvier_des_Flandres",
+    "13": "Brabancon_griffon",
+    "14": "Brittany_spaniel",
+    "15": "Cardigan",
+    "16": "Chesapeake_Bay_retriever",
+    "17": "Chihuahua",
+    "18": "Dandie_Dinmont",
+    "19": "Doberman",
+    "2": "Airedale",
+    "20": "English_foxhound",
+    "21": "English_setter",
+    "22": "English_springer",
+    "23": "EntleBucher",
+    "24": "Eskimo_dog",
+    "25": "French_bulldog",
+    "26": "German_shepherd",
+    "27": "German_short",
+    "28": "Gordon_setter",
+    "29": "Great_Dane",
+    "3": "American_Staffordshire_terrier",
+    "30": "Great_Pyrenees",
+    "31": "Greater_Swiss_Mountain_dog",
+    "32": "Ibizan_hound",
+    "33": "Irish_setter",
+    "34": "Irish_terrier",
+    "35": "Irish_water_spaniel",
+    "36": "Irish_wolfhound",
+    "37": "Italian_greyhound",
+    "38": "Japanese_spaniel",
+    "39": "Kerry_blue_terrier",
+    "4": "Appenzeller",
+    "40": "Labrador_retriever",
+    "41": "Lakeland_terrier",
+    "42": "Leonberg",
+    "43": "Lhasa",
+    "44": "Maltese_dog",
+    "45": "Mexican_hairless",
+    "46": "Newfoundland",
+    "47": "Norfolk_terrier",
+    "48": "Norwegian_elkhound",
+    "49": "Norwich_terrier",
+    "5": "Australian_terrier",
+    "50": "Old_English_sheepdog",
+    "51": "Pekinese",
+    "52": "Pembroke",
+    "53": "Pomeranian",
+    "54": "Rhodesian_ridgeback",
+    "55": "Rottweiler",
+    "56": "Saint_Bernard",
+    "57": "Saluki",
+    "58": "Samoyed",
+    "59": "Scotch_terrier",
+    "6": "Bedlington_terrier",
+    "60": "Scottish_deerhound",
+    "61": "Sealyham_terrier",
+    "62": "Shetland_sheepdog",
+    "63": "Shih",
+    "64": "Siberian_husky",
+    "65": "Staffordshire_bullterrier",
+    "66": "Sussex_spaniel",
+    "67": "Tibetan_mastiff",
+    "68": "Tibetan_terrier",
+    "69": "Walker_hound",
+    "7": "Bernese_mountain_dog",
+    "70": "Weimaraner",
+    "71": "Welsh_springer_spaniel",
+    "72": "West_Highland_white_terrier",
+    "73": "Yorkshire_terrier",
+    "74": "affenpinscher",
+    "75": "basenji",
+    "76": "basset",
+    "77": "beagle",
+    "78": "black",
+    "79": "bloodhound",
+    "8": "Blenheim_spaniel",
+    "80": "bluetick",
+    "81": "borzoi",
+    "82": "boxer",
+    "83": "briard",
+    "84": "bull_mastiff",
+    "85": "cairn",
+    "86": "chow",
+    "87": "clumber",
+    "88": "cocker_spaniel",
+    "89": "collie",
+    "9": "Border_collie",
+    "90": "curly",
+    "91": "dhole",
+    "92": "dingo",
+    "93": "flat",
+    "94": "giant_schnauzer",
+    "95": "golden_retriever",
+    "96": "groenendael",
+    "97": "keeshond",
+    "98": "kelpie",
+    "99": "komondor"
+  },
+  "label2id": {
+    "Afghan_hound": "0",
+    "African_hunting_dog": "1",
+    "Airedale": "2",
+    "American_Staffordshire_terrier": "3",
+    "Appenzeller": "4",
+    "Australian_terrier": "5",
+    "Bedlington_terrier": "6",
+    "Bernese_mountain_dog": "7",
+    "Blenheim_spaniel": "8",
+    "Border_collie": "9",
+    "Border_terrier": "10",
+    "Boston_bull": "11",
+    "Bouvier_des_Flandres": "12",
+    "Brabancon_griffon": "13",
+    "Brittany_spaniel": "14",
+    "Cardigan": "15",
+    "Chesapeake_Bay_retriever": "16",
+    "Chihuahua": "17",
+    "Dandie_Dinmont": "18",
+    "Doberman": "19",
+    "English_foxhound": "20",
+    "English_setter": "21",
+    "English_springer": "22",
+    "EntleBucher": "23",
+    "Eskimo_dog": "24",
+    "French_bulldog": "25",
+    "German_shepherd": "26",
+    "German_short": "27",
+    "Gordon_setter": "28",
+    "Great_Dane": "29",
+    "Great_Pyrenees": "30",
+    "Greater_Swiss_Mountain_dog": "31",
+    "Ibizan_hound": "32",
+    "Irish_setter": "33",
+    "Irish_terrier": "34",
+    "Irish_water_spaniel": "35",
+    "Irish_wolfhound": "36",
+    "Italian_greyhound": "37",
+    "Japanese_spaniel": "38",
+    "Kerry_blue_terrier": "39",
+    "Labrador_retriever": "40",
+    "Lakeland_terrier": "41",
+    "Leonberg": "42",
+    "Lhasa": "43",
+    "Maltese_dog": "44",
+    "Mexican_hairless": "45",
+    "Newfoundland": "46",
+    "Norfolk_terrier": "47",
+    "Norwegian_elkhound": "48",
+    "Norwich_terrier": "49",
+    "Old_English_sheepdog": "50",
+    "Pekinese": "51",
+    "Pembroke": "52",
+    "Pomeranian": "53",
+    "Rhodesian_ridgeback": "54",
+    "Rottweiler": "55",
+    "Saint_Bernard": "56",
+    "Saluki": "57",
+    "Samoyed": "58",
+    "Scotch_terrier": "59",
+    "Scottish_deerhound": "60",
+    "Sealyham_terrier": "61",
+    "Shetland_sheepdog": "62",
+    "Shih": "63",
+    "Siberian_husky": "64",
+    "Staffordshire_bullterrier": "65",
+    "Sussex_spaniel": "66",
+    "Tibetan_mastiff": "67",
+    "Tibetan_terrier": "68",
+    "Walker_hound": "69",
+    "Weimaraner": "70",
+    "Welsh_springer_spaniel": "71",
+    "West_Highland_white_terrier": "72",
+    "Yorkshire_terrier": "73",
+    "affenpinscher": "74",
+    "basenji": "75",
+    "basset": "76",
+    "beagle": "77",
+    "black": "78",
+    "bloodhound": "79",
+    "bluetick": "80",
+    "borzoi": "81",
+    "boxer": "82",
+    "briard": "83",
+    "bull_mastiff": "84",
+    "cairn": "85",
+    "chow": "86",
+    "clumber": "87",
+    "cocker_spaniel": "88",
+    "collie": "89",
+    "curly": "90",
+    "dhole": "91",
+    "dingo": "92",
+    "flat": "93",
+    "giant_schnauzer": "94",
+    "golden_retriever": "95",
+    "groenendael": "96",
+    "keeshond": "97",
+    "kelpie": "98",
+    "komondor": "99",
+    "kuvasz": "100",
+    "malamute": "101",
+    "malinois": "102",
+    "miniature_pinscher": "103",
+    "miniature_poodle": "104",
+    "miniature_schnauzer": "105",
+    "otterhound": "106",
+    "papillon": "107",
+    "pug": "108",
+    "redbone": "109",
+    "schipperke": "110",
+    "silky_terrier": "111",
+    "soft": "112",
+    "standard_poodle": "113",
+    "standard_schnauzer": "114",
+    "toy_poodle": "115",
+    "toy_terrier": "116",
+    "vizsla": "117",
+    "whippet": "118",
+    "wire": "119"
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "problem_type": "single_label_classification",
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "torch_dtype": "float32",
+  "transformers_version": "4.37.2"
+}

model.safetensors

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+size 95270232

preprocessor_config.json

@@ -0,0 +1,22 @@
+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}

training_args.bin

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