Model save

README.md

@@ -1,8 +1,7 @@
 ---
 license: apache-2.0
-base_model: microsoft/swinv2-tiny-patch4-window16-256
+base_model: google/vit-base-patch16-224-in21k
 tags:
-- image-classification
 - generated_from_trainer
 datasets:
 - imagefolder
@@ -15,7 +14,7 @@ model-index:
       name: Image Classification
       type: image-classification
     dataset:
-      name: agent_action_class
+      name: imagefolder
       type: imagefolder
       config: default
       split: train
@@ -23,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.7895238095238095
+      value: 0.8019047619047619
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # Action_agent
 
-This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window16-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window16-256) on the agent_action_class dataset.
+This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6309
-- Accuracy: 0.7895
+- Loss: 0.6758
+- Accuracy: 0.8019
 
 ## Model description
 
@@ -59,43 +58,74 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 10
+- num_epochs: 20
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.039         | 0.32  | 100  | 1.7706          | 0.4848   |
-| 1.3695        | 0.64  | 200  | 1.0886          | 0.6457   |
-| 1.099         | 0.96  | 300  | 0.9092          | 0.68     |
-| 1.0011        | 1.27  | 400  | 0.8183          | 0.7171   |
-| 0.8437        | 1.59  | 500  | 0.7674          | 0.7190   |
-| 0.8613        | 1.91  | 600  | 0.7168          | 0.7410   |
-| 0.7427        | 2.23  | 700  | 0.7270          | 0.7352   |
-| 0.693         | 2.55  | 800  | 0.6801          | 0.7676   |
-| 0.7789        | 2.87  | 900  | 0.6832          | 0.7590   |
-| 0.6863        | 3.18  | 1000 | 0.6655          | 0.7752   |
-| 0.6437        | 3.5   | 1100 | 0.6382          | 0.7771   |
-| 0.6741        | 3.82  | 1200 | 0.6446          | 0.7790   |
-| 0.5871        | 4.14  | 1300 | 0.6551          | 0.7838   |
-| 0.6051        | 4.46  | 1400 | 0.6970          | 0.7638   |
-| 0.5175        | 4.78  | 1500 | 0.6553          | 0.7790   |
-| 0.5795        | 5.1   | 1600 | 0.6667          | 0.7771   |
-| 0.4919        | 5.41  | 1700 | 0.6317          | 0.7905   |
-| 0.4986        | 5.73  | 1800 | 0.6486          | 0.7810   |
-| 0.5104        | 6.05  | 1900 | 0.6700          | 0.7743   |
-| 0.4919        | 6.37  | 2000 | 0.6528          | 0.7819   |
-| 0.5144        | 6.69  | 2100 | 0.6355          | 0.7876   |
-| 0.5554        | 7.01  | 2200 | 0.6552          | 0.7771   |
-| 0.5389        | 7.32  | 2300 | 0.6361          | 0.7876   |
-| 0.5751        | 7.64  | 2400 | 0.6377          | 0.7905   |
-| 0.4743        | 7.96  | 2500 | 0.6417          | 0.7867   |
-| 0.4519        | 8.28  | 2600 | 0.6309          | 0.7895   |
-| 0.5058        | 8.6   | 2700 | 0.6453          | 0.7867   |
-| 0.4754        | 8.92  | 2800 | 0.6414          | 0.7905   |
-| 0.4637        | 9.24  | 2900 | 0.6330          | 0.7905   |
-| 0.5028        | 9.55  | 3000 | 0.6418          | 0.7857   |
-| 0.4227        | 9.87  | 3100 | 0.6412          | 0.7914   |
+| 2.1987        | 0.32  | 100  | 2.1640          | 0.3914   |
+| 1.9807        | 0.64  | 200  | 1.9169          | 0.6143   |
+| 1.6738        | 0.96  | 300  | 1.6148          | 0.72     |
+| 1.4828        | 1.27  | 400  | 1.3861          | 0.7705   |
+| 1.2768        | 1.59  | 500  | 1.2412          | 0.7590   |
+| 1.1759        | 1.91  | 600  | 1.1169          | 0.7914   |
+| 1.0314        | 2.23  | 700  | 1.0599          | 0.7762   |
+| 0.9702        | 2.55  | 800  | 0.9640          | 0.8105   |
+| 0.9559        | 2.87  | 900  | 0.9138          | 0.8076   |
+| 0.858         | 3.18  | 1000 | 0.8605          | 0.8248   |
+| 0.7858        | 3.5   | 1100 | 0.8164          | 0.8371   |
+| 0.7898        | 3.82  | 1200 | 0.7917          | 0.8333   |
+| 0.6909        | 4.14  | 1300 | 0.7995          | 0.8038   |
+| 0.6619        | 4.46  | 1400 | 0.8194          | 0.7829   |
+| 0.6457        | 4.78  | 1500 | 0.7536          | 0.8086   |
+| 0.6155        | 5.1   | 1600 | 0.7212          | 0.8257   |
+| 0.5511        | 5.41  | 1700 | 0.7274          | 0.8095   |
+| 0.5486        | 5.73  | 1800 | 0.7048          | 0.8286   |
+| 0.5679        | 6.05  | 1900 | 0.7124          | 0.8181   |
+| 0.4914        | 6.37  | 2000 | 0.7277          | 0.8010   |
+| 0.525         | 6.69  | 2100 | 0.6971          | 0.8124   |
+| 0.5081        | 7.01  | 2200 | 0.6869          | 0.8162   |
+| 0.5072        | 7.32  | 2300 | 0.6837          | 0.8076   |
+| 0.4702        | 7.64  | 2400 | 0.6736          | 0.8152   |
+| 0.4303        | 7.96  | 2500 | 0.6693          | 0.8105   |
+| 0.3916        | 8.28  | 2600 | 0.6487          | 0.8238   |
+| 0.4002        | 8.6   | 2700 | 0.6661          | 0.8162   |
+| 0.3965        | 8.92  | 2800 | 0.6611          | 0.8143   |
+| 0.3946        | 9.24  | 2900 | 0.6523          | 0.8143   |
+| 0.3794        | 9.55  | 3000 | 0.6616          | 0.8048   |
+| 0.3257        | 9.87  | 3100 | 0.6717          | 0.8029   |
+| 0.4175        | 10.19 | 3200 | 0.6530          | 0.8057   |
+| 0.3559        | 10.51 | 3300 | 0.6883          | 0.7886   |
+| 0.3824        | 10.83 | 3400 | 0.6611          | 0.8      |
+| 0.3589        | 11.15 | 3500 | 0.6659          | 0.8019   |
+| 0.3299        | 11.46 | 3600 | 0.6819          | 0.7962   |
+| 0.3736        | 11.78 | 3700 | 0.6405          | 0.8114   |
+| 0.3576        | 12.1  | 3800 | 0.6725          | 0.7962   |
+| 0.3454        | 12.42 | 3900 | 0.7025          | 0.7943   |
+| 0.3049        | 12.74 | 4000 | 0.6439          | 0.8133   |
+| 0.3363        | 13.06 | 4100 | 0.6352          | 0.8143   |
+| 0.3273        | 13.38 | 4200 | 0.6795          | 0.7886   |
+| 0.283         | 13.69 | 4300 | 0.6705          | 0.8      |
+| 0.2607        | 14.01 | 4400 | 0.6732          | 0.7914   |
+| 0.3174        | 14.33 | 4500 | 0.6691          | 0.8048   |
+| 0.3189        | 14.65 | 4600 | 0.6602          | 0.8038   |
+| 0.2862        | 14.97 | 4700 | 0.6801          | 0.7933   |
+| 0.2895        | 15.29 | 4800 | 0.6579          | 0.8038   |
+| 0.263         | 15.61 | 4900 | 0.6688          | 0.8      |
+| 0.3214        | 15.92 | 5000 | 0.6547          | 0.8057   |
+| 0.2867        | 16.24 | 5100 | 0.6775          | 0.7924   |
+| 0.2242        | 16.56 | 5200 | 0.6378          | 0.8086   |
+| 0.2839        | 16.88 | 5300 | 0.6761          | 0.7990   |
+| 0.2424        | 17.2  | 5400 | 0.6386          | 0.8124   |
+| 0.2666        | 17.52 | 5500 | 0.6493          | 0.8133   |
+| 0.2259        | 17.83 | 5600 | 0.6514          | 0.8048   |
+| 0.2533        | 18.15 | 5700 | 0.6676          | 0.8      |
+| 0.2697        | 18.47 | 5800 | 0.6705          | 0.8010   |
+| 0.2558        | 18.79 | 5900 | 0.6750          | 0.8076   |
+| 0.2469        | 19.11 | 6000 | 0.6751          | 0.7990   |
+| 0.284         | 19.43 | 6100 | 0.6738          | 0.7981   |
+| 0.2534        | 19.75 | 6200 | 0.6758          | 0.8019   |
 
 
 ### Framework versions

config.json

@@ -1,18 +1,10 @@
 {
-  "_name_or_path": "microsoft/swinv2-tiny-patch4-window16-256",
+  "_name_or_path": "google/vit-base-patch16-224-in21k",
   "architectures": [
-    "Swinv2ForImageClassification"
+    "ViTForImageClassification"
   ],
   "attention_probs_dropout_prob": 0.0,
-  "depths": [
-    2,
-    2,
-    6,
-    2
-  ],
-  "drop_path_rate": 0.1,
-  "embed_dim": 96,
-  "encoder_stride": 32,
+  "encoder_stride": 16,
   "hidden_act": "gelu",
   "hidden_dropout_prob": 0.0,
   "hidden_size": 768,
@@ -28,8 +20,9 @@
     "8": "\u09b2\u09c7\u0996\u09be",
     "9": "\u09b9\u09be\u0981\u099f\u09be"
   },
-  "image_size": 256,
+  "image_size": 224,
   "initializer_range": 0.02,
+  "intermediate_size": 3072,
   "label2id": {
     "\u0995\u09a5\u09be_\u09ac\u09b2\u09be": "0",
     "\u0995\u09ae\u09cd\u09aa\u09bf\u0989\u099f\u09be\u09b0_\u09ac\u09cd\u09af\u09ac\u09b9\u09be\u09b0_\u0995\u09b0\u09be": "1",
@@ -42,42 +35,14 @@
     "\u09b2\u09c7\u0996\u09be": "8",
     "\u09b9\u09be\u0981\u099f\u09be": "9"
   },
-  "layer_norm_eps": 1e-05,
-  "mlp_ratio": 4.0,
-  "model_type": "swinv2",
+  "layer_norm_eps": 1e-12,
+  "model_type": "vit",
+  "num_attention_heads": 12,
   "num_channels": 3,
-  "num_heads": [
-    3,
-    6,
-    12,
-    24
-  ],
-  "num_layers": 4,
-  "out_features": [
-    "stage4"
-  ],
-  "out_indices": [
-    4
-  ],
-  "patch_size": 4,
-  "path_norm": true,
-  "pretrained_window_sizes": [
-    0,
-    0,
-    0,
-    0
-  ],
+  "num_hidden_layers": 12,
+  "patch_size": 16,
   "problem_type": "single_label_classification",
   "qkv_bias": true,
-  "stage_names": [
-    "stem",
-    "stage1",
-    "stage2",
-    "stage3",
-    "stage4"
-  ],
   "torch_dtype": "float32",
-  "transformers_version": "4.39.3",
-  "use_absolute_embeddings": false,
-  "window_size": 16
+  "transformers_version": "4.39.3"
 }

model.safetensors

@@ -1,3 +1,3 @@
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-oid sha256:2b5cf3b87b343cd43304129258627ec15995b5efe57f624c30058abd1a85104a
-size 110374752
+oid sha256:31983f56343634d1a566ca12a56db4837634bdeac1d25f16d1410f817d230089
+size 343248584

preprocessor_config.json

@@ -17,20 +17,20 @@
   "do_rescale": true,
   "do_resize": true,
   "image_mean": [
-    0.485,
-    0.456,
-    0.406
+    0.5,
+    0.5,
+    0.5
   ],
   "image_processor_type": "ViTImageProcessor",
   "image_std": [
-    0.229,
-    0.224,
-    0.225
+    0.5,
+    0.5,
+    0.5
   ],
-  "resample": 3,
+  "resample": 2,
   "rescale_factor": 0.00392156862745098,
   "size": {
-    "height": 256,
-    "width": 256
+    "height": 224,
+    "width": 224
   }
 }

runs/Apr23_06-49-05_ca94fea6a63f/events.out.tfevents.1713854946.ca94fea6a63f.34.0

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+size 114142

training_args.bin

@@ -1,3 +1,3 @@
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-oid sha256:7e145019e5e9eb49ac1a9542b4cc2430a5e37f69fa201e50c7d9e96b4bb660be
+oid sha256:ad13277320cee32735fa755cc8392846fb447972a0cef9dae2890aaa91beb780
 size 4920