add labels

all_results.json

@@ -1,12 +1,12 @@
 {
     "epoch": 6.0,
-    "eval_accuracy": 0.518796992481203,
-    "eval_loss": 0.9727851152420044,
-    "eval_runtime": 0.6952,
-    "eval_samples_per_second": 191.321,
-    "eval_steps_per_second": 24.455,
-    "train_loss": 0.9793546272046638,
-    "train_runtime": 46.4278,
-    "train_samples_per_second": 133.627,
-    "train_steps_per_second": 4.265
+    "eval_accuracy": 0.5263157894736842,
+    "eval_loss": 0.9798622727394104,
+    "eval_runtime": 0.5254,
+    "eval_samples_per_second": 253.138,
+    "eval_steps_per_second": 32.356,
+    "train_loss": 0.9850856896602747,
+    "train_runtime": 45.3029,
+    "train_samples_per_second": 136.945,
+    "train_steps_per_second": 4.371
 }

config.json

@@ -8,20 +8,21 @@
   ],
   "downsample_in_first_stage": false,
   "embedding_size": 64,
+  "finetuning_task": "image-classification",
   "hidden_act": "relu",
   "hidden_sizes": [
     32,
     64
   ],
   "id2label": {
-    "0": "LABEL_0",
-    "1": "LABEL_1",
-    "2": "LABEL_2"
+    "0": "angular_leaf_spot",
+    "1": "bean_rust",
+    "2": "healthy"
   },
   "label2id": {
-    "LABEL_0": 0,
-    "LABEL_1": 1,
-    "LABEL_2": 2
+    "angular_leaf_spot": "0",
+    "bean_rust": "1",
+    "healthy": "2"
   },
   "layer_type": "basic",
   "model_type": "resnet",

eval_results.json

@@ -1,8 +1,8 @@
 {
     "epoch": 6.0,
-    "eval_accuracy": 0.518796992481203,
-    "eval_loss": 0.9727851152420044,
-    "eval_runtime": 0.6952,
-    "eval_samples_per_second": 191.321,
-    "eval_steps_per_second": 24.455
+    "eval_accuracy": 0.5263157894736842,
+    "eval_loss": 0.9798622727394104,
+    "eval_runtime": 0.5254,
+    "eval_samples_per_second": 253.138,
+    "eval_steps_per_second": 32.356
 }

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:fed11a151a68d9df16a542bac37db8525a7832fdf78c3bb56c3b2a409a717e2f
+oid sha256:e97a7d6e40e590c8dc7ffdafc47eb810e50b51a33a98732caa5bd854c31fadc0
 size 761689

train.py

@@ -106,12 +106,23 @@ def main():
         do_resize=False, do_normalize=False, image_mean=[0.45], image_std=[0.22]
     )
 
+    # Prepare label mappings.
+    # We'll include these in the model's config to get human readable labels in the Inference API.
+    labels = dataset["train"].features["labels"].names
+    label2id, id2label = dict(), dict()
+    for i, label in enumerate(labels):
+        label2id[label] = str(i)
+        id2label[str(i)] = label
+
     config = ResNetConfig(
         num_channels=1,
         layer_type="basic",
         depths=[2, 2],
         hidden_sizes=[32, 64],
         num_labels=3,
+        label2id=label2id,
+        id2label=id2label,
+        finetuning_task="image-classification",
     )
 
     model = ResNetForImageClassification(config)

train_results.json

@@ -1,7 +1,7 @@
 {
     "epoch": 6.0,
-    "train_loss": 0.9793546272046638,
-    "train_runtime": 46.4278,
-    "train_samples_per_second": 133.627,
-    "train_steps_per_second": 4.265
+    "train_loss": 0.9850856896602747,
+    "train_runtime": 45.3029,
+    "train_samples_per_second": 136.945,
+    "train_steps_per_second": 4.371
 }

trainer_state.json

@@ -11,10 +11,10 @@
       "epoch": 6.0,
       "step": 198,
       "total_flos": 1708758414000000.0,
-      "train_loss": 0.9793546272046638,
-      "train_runtime": 46.4278,
-      "train_samples_per_second": 133.627,
-      "train_steps_per_second": 4.265
+      "train_loss": 0.9850856896602747,
+      "train_runtime": 45.3029,
+      "train_samples_per_second": 136.945,
+      "train_steps_per_second": 4.371
     }
   ],
   "max_steps": 198,

training_args.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:7263e66f73eef0346825fd1736d362a11c375b16f528efa9b6d6c32e654631d4
+oid sha256:70d8482fcb9abee83a681eed3ba240f26ef087833064a1271f60d549c4fa686a
 size 3247