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Raihan004
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Action_model

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Files changed (6) hide show
  1. README.md +68 -37
  2. config.json +9 -9
  3. model.safetensors +1 -1
  4. preprocessor_config.json +21 -8
  5. runs/Apr18_13-48-02_895abc48f543/events.out.tfevents.1713448213.895abc48f543.34.0 +3 -0
  6. training_args.bin +2 -2
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
22
  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.7495238095238095
26
  ---
27
 
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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  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.
34
  It achieves the following results on the evaluation set:
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- - Loss: 0.9816
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- - Accuracy: 0.7495
37
 
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  ## Model description
39
 
@@ -58,49 +58,80 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 5
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  - mixed_precision_training: Native AMP
63
 
64
  ### Training results
65
 
66
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
67
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
68
- | 1.4818 | 0.16 | 100 | 1.2573 | 0.7219 |
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- | 1.0598 | 0.32 | 200 | 0.9673 | 0.7419 |
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- | 0.9126 | 0.48 | 300 | 0.8612 | 0.7514 |
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- | 0.6733 | 0.64 | 400 | 0.9162 | 0.7038 |
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- | 0.7302 | 0.8 | 500 | 0.9483 | 0.7124 |
73
- | 0.7024 | 0.96 | 600 | 0.7318 | 0.7752 |
74
- | 0.5469 | 1.11 | 700 | 1.0155 | 0.6990 |
75
- | 0.4757 | 1.27 | 800 | 0.8299 | 0.7438 |
76
- | 0.4618 | 1.43 | 900 | 0.7697 | 0.7648 |
77
- | 0.5045 | 1.59 | 1000 | 0.9454 | 0.7152 |
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- | 0.4229 | 1.75 | 1100 | 0.7776 | 0.7629 |
79
- | 0.3894 | 1.91 | 1200 | 0.8798 | 0.7495 |
80
- | 0.3432 | 2.07 | 1300 | 0.8088 | 0.7590 |
81
- | 0.3212 | 2.23 | 1400 | 0.7810 | 0.7733 |
82
- | 0.3043 | 2.39 | 1500 | 1.0076 | 0.7295 |
83
- | 0.255 | 2.55 | 1600 | 0.8672 | 0.7590 |
84
- | 0.2834 | 2.71 | 1700 | 0.9165 | 0.7438 |
85
- | 0.341 | 2.87 | 1800 | 0.7474 | 0.7838 |
86
- | 0.1858 | 3.03 | 1900 | 1.0221 | 0.7229 |
87
- | 0.2463 | 3.18 | 2000 | 0.8464 | 0.7829 |
88
- | 0.2661 | 3.34 | 2100 | 0.9434 | 0.7476 |
89
- | 0.2367 | 3.5 | 2200 | 0.9285 | 0.76 |
90
- | 0.2299 | 3.66 | 2300 | 0.9777 | 0.7486 |
91
- | 0.221 | 3.82 | 2400 | 0.9455 | 0.7533 |
92
- | 0.2799 | 3.98 | 2500 | 1.0371 | 0.74 |
93
- | 0.1185 | 4.14 | 2600 | 1.0378 | 0.7390 |
94
- | 0.1405 | 4.3 | 2700 | 1.0870 | 0.7352 |
95
- | 0.263 | 4.46 | 2800 | 1.1081 | 0.7276 |
96
- | 0.254 | 4.62 | 2900 | 1.0279 | 0.7381 |
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- | 0.158 | 4.78 | 3000 | 0.9646 | 0.7514 |
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- | 0.1496 | 4.94 | 3100 | 0.9816 | 0.7495 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
99
 
100
 
101
  ### Framework versions
102
 
103
- - Transformers 4.38.2
104
- - Pytorch 2.2.1+cu121
105
  - Datasets 2.18.0
106
  - Tokenizers 0.15.2
 
22
  metrics:
23
  - name: Accuracy
24
  type: accuracy
25
+ value: 0.7619047619047619
26
  ---
27
 
28
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
32
 
33
  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.
34
  It achieves the following results on the evaluation set:
35
+ - Loss: 1.2147
36
+ - Accuracy: 0.7619
37
 
38
  ## Model description
39
 
 
58
  - seed: 42
59
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
60
  - lr_scheduler_type: linear
61
+ - num_epochs: 10
62
  - mixed_precision_training: Native AMP
63
 
64
  ### Training results
65
 
66
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
67
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
68
+ | 0.1624 | 0.16 | 100 | 1.0534 | 0.7638 |
69
+ | 0.2926 | 0.32 | 200 | 1.3484 | 0.6867 |
70
+ | 0.159 | 0.48 | 300 | 0.9484 | 0.7724 |
71
+ | 0.2145 | 0.64 | 400 | 1.0014 | 0.7476 |
72
+ | 0.1889 | 0.8 | 500 | 1.0321 | 0.7457 |
73
+ | 0.3064 | 0.96 | 600 | 1.0795 | 0.7314 |
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+ | 0.2195 | 1.11 | 700 | 0.9886 | 0.7629 |
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+ | 0.2982 | 1.27 | 800 | 1.0292 | 0.7590 |
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+ | 0.2477 | 1.43 | 900 | 1.2391 | 0.7248 |
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+ | 0.3076 | 1.59 | 1000 | 1.1326 | 0.7324 |
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+ | 0.1863 | 1.75 | 1100 | 1.2596 | 0.7048 |
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+ | 0.2577 | 1.91 | 1200 | 1.0649 | 0.7610 |
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+ | 0.1491 | 2.07 | 1300 | 1.1044 | 0.7562 |
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+ | 0.2635 | 2.23 | 1400 | 1.1965 | 0.7448 |
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+ | 0.2597 | 2.39 | 1500 | 1.2241 | 0.7429 |
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+ | 0.2468 | 2.55 | 1600 | 1.1452 | 0.7390 |
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+ | 0.216 | 2.71 | 1700 | 1.2419 | 0.7276 |
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+ | 0.1971 | 2.87 | 1800 | 1.1883 | 0.7362 |
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+ | 0.2071 | 3.03 | 1900 | 1.4659 | 0.6952 |
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+ | 0.1535 | 3.18 | 2000 | 1.0239 | 0.7724 |
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+ | 0.1842 | 3.34 | 2100 | 1.1967 | 0.7390 |
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+ | 0.2087 | 3.5 | 2200 | 1.1403 | 0.7467 |
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+ | 0.1658 | 3.66 | 2300 | 1.2901 | 0.7343 |
91
+ | 0.1159 | 3.82 | 2400 | 1.1826 | 0.7438 |
92
+ | 0.1498 | 3.98 | 2500 | 1.2627 | 0.7419 |
93
+ | 0.135 | 4.14 | 2600 | 1.1383 | 0.76 |
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+ | 0.1492 | 4.3 | 2700 | 1.2310 | 0.7343 |
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+ | 0.0982 | 4.46 | 2800 | 1.4144 | 0.7105 |
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+ | 0.1256 | 4.62 | 2900 | 1.3513 | 0.7171 |
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+ | 0.1544 | 4.78 | 3000 | 1.4280 | 0.7019 |
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+ | 0.0858 | 4.94 | 3100 | 1.2231 | 0.7429 |
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+ | 0.1049 | 5.1 | 3200 | 1.2775 | 0.7352 |
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+ | 0.1361 | 5.25 | 3300 | 1.2840 | 0.7429 |
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+ | 0.1505 | 5.41 | 3400 | 1.3373 | 0.7390 |
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+ | 0.1244 | 5.57 | 3500 | 1.2959 | 0.7438 |
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+ | 0.1114 | 5.73 | 3600 | 1.3181 | 0.7381 |
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+ | 0.0851 | 5.89 | 3700 | 1.3288 | 0.7457 |
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+ | 0.0799 | 6.05 | 3800 | 1.1859 | 0.76 |
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+ | 0.1331 | 6.21 | 3900 | 1.2544 | 0.7371 |
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+ | 0.121 | 6.37 | 4000 | 1.2186 | 0.7533 |
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+ | 0.1276 | 6.53 | 4100 | 1.2964 | 0.7324 |
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+ | 0.1194 | 6.69 | 4200 | 1.1907 | 0.7590 |
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+ | 0.1649 | 6.85 | 4300 | 1.4679 | 0.7105 |
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+ | 0.0558 | 7.01 | 4400 | 1.2028 | 0.7533 |
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+ | 0.0687 | 7.17 | 4500 | 1.3242 | 0.7381 |
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+ | 0.1419 | 7.32 | 4600 | 1.2328 | 0.76 |
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+ | 0.0901 | 7.48 | 4700 | 1.1861 | 0.7676 |
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+ | 0.1181 | 7.64 | 4800 | 1.4031 | 0.7352 |
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+ | 0.1272 | 7.8 | 4900 | 1.3608 | 0.7438 |
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+ | 0.0979 | 7.96 | 5000 | 1.3098 | 0.7495 |
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+ | 0.0805 | 8.12 | 5100 | 1.2445 | 0.7533 |
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+ | 0.0354 | 8.28 | 5200 | 1.2345 | 0.7581 |
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+ | 0.0499 | 8.44 | 5300 | 1.1776 | 0.7571 |
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+ | 0.1046 | 8.6 | 5400 | 1.1939 | 0.76 |
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+ | 0.0912 | 8.76 | 5500 | 1.2373 | 0.7486 |
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+ | 0.0589 | 8.92 | 5600 | 1.2165 | 0.7552 |
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+ | 0.0829 | 9.08 | 5700 | 1.2684 | 0.7505 |
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+ | 0.0897 | 9.24 | 5800 | 1.2467 | 0.7552 |
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+ | 0.1114 | 9.39 | 5900 | 1.2303 | 0.7571 |
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+ | 0.0712 | 9.55 | 6000 | 1.1997 | 0.7638 |
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+ | 0.0621 | 9.71 | 6100 | 1.2094 | 0.7629 |
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+ | 0.037 | 9.87 | 6200 | 1.2147 | 0.7619 |
130
 
131
 
132
  ### Framework versions
133
 
134
+ - Transformers 4.39.3
135
+ - Pytorch 2.1.2
136
  - Datasets 2.18.0
137
  - Tokenizers 0.15.2
config.json CHANGED
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@@ -44,5 +44,5 @@
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  "problem_type": "single_label_classification",
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- "transformers_version": "4.38.2"
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  "problem_type": "single_label_classification",
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