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Image Classification
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vit
Generated from Trainer
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Skullly commited on
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End of training

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Files changed (3) hide show
  1. README.md +25 -25
  2. all_results.json +5 -5
  3. eval_results.json +5 -5
README.md CHANGED
@@ -1,6 +1,6 @@
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  ---
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  license: apache-2.0
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- base_model: google/efficientnet-b2
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -15,10 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # results
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- This model is a fine-tuned version of [google/efficientnet-b2](https://huggingface.co/google/efficientnet-b2) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1078
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- - Accuracy: 0.9598
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  ## Model description
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@@ -52,27 +52,27 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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- | 0.7059 | 0.1829 | 100 | 0.6640 | 0.6232 |
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- | 0.6189 | 0.3657 | 200 | 0.5881 | 0.7547 |
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- | 0.4646 | 0.5486 | 300 | 0.4643 | 0.8030 |
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- | 0.317 | 0.7314 | 400 | 0.3648 | 0.8457 |
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- | 0.2206 | 0.9143 | 500 | 0.2737 | 0.8874 |
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- | 0.1572 | 1.0971 | 600 | 0.2665 | 0.8787 |
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- | 0.1102 | 1.28 | 700 | 0.2336 | 0.8902 |
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- | 0.0787 | 1.4629 | 800 | 0.1256 | 0.9518 |
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- | 0.058 | 1.6457 | 900 | 0.1807 | 0.9211 |
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- | 0.0506 | 1.8286 | 1000 | 0.1146 | 0.9547 |
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- | 0.0385 | 2.0114 | 1100 | 0.1418 | 0.9402 |
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- | 0.0273 | 2.1943 | 1200 | 0.0924 | 0.9639 |
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- | 0.021 | 2.3771 | 1300 | 0.2166 | 0.9093 |
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- | 0.019 | 2.56 | 1400 | 0.2138 | 0.9158 |
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- | 0.0174 | 2.7429 | 1500 | 0.1078 | 0.9598 |
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- | 0.0161 | 2.9257 | 1600 | 0.0846 | 0.9686 |
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- | 0.0147 | 3.1086 | 1700 | 0.1207 | 0.9561 |
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- | 0.0122 | 3.2914 | 1800 | 0.1366 | 0.9476 |
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- | 0.0112 | 3.4743 | 1900 | 0.2256 | 0.9077 |
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- | 0.0109 | 3.6571 | 2000 | 0.1596 | 0.9416 |
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- | 0.0101 | 3.84 | 2100 | 0.2561 | 0.9018 |
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  ### Framework versions
 
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  ---
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  license: apache-2.0
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+ base_model: google/vit-base-patch16-224-in21k
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  # results
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1114
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+ - Accuracy: 0.9687
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | 0.6639 | 0.1829 | 100 | 0.6155 | 0.6554 |
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+ | 0.4191 | 0.3657 | 200 | 0.3088 | 0.8959 |
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+ | 0.1698 | 0.5486 | 300 | 0.5321 | 0.7281 |
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+ | 0.0749 | 0.7314 | 400 | 0.5087 | 0.7900 |
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+ | 0.0484 | 0.9143 | 500 | 0.4649 | 0.8185 |
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+ | 0.0323 | 1.0971 | 600 | 0.6888 | 0.762 |
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+ | 0.0264 | 1.28 | 700 | 0.1395 | 0.9513 |
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+ | 0.0224 | 1.4629 | 800 | 0.0661 | 0.9776 |
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+ | 0.02 | 1.6457 | 900 | 0.1173 | 0.9581 |
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+ | 0.0168 | 1.8286 | 1000 | 0.3498 | 0.889 |
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+ | 0.013 | 2.0114 | 1100 | 0.1053 | 0.9655 |
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+ | 0.0087 | 2.1943 | 1200 | 0.3601 | 0.8947 |
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+ | 0.0081 | 2.3771 | 1300 | 0.1508 | 0.9535 |
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+ | 0.0073 | 2.56 | 1400 | 0.2090 | 0.9390 |
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+ | 0.0056 | 2.7429 | 1500 | 0.1136 | 0.9649 |
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+ | 0.005 | 2.9257 | 1600 | 0.2656 | 0.9206 |
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+ | 0.0036 | 3.1086 | 1700 | 0.1320 | 0.9595 |
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+ | 0.002 | 3.2914 | 1800 | 0.1068 | 0.9686 |
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+ | 0.0018 | 3.4743 | 1900 | 0.1091 | 0.9690 |
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+ | 0.0019 | 3.6571 | 2000 | 0.1114 | 0.9687 |
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+ | 0.0018 | 3.84 | 2100 | 0.0968 | 0.9719 |
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  ### Framework versions
all_results.json CHANGED
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  {
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  "epoch": 3.9936,
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- "eval_accuracy": 0.9597666666666667,
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- "eval_loss": 0.10777818411588669,
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- "eval_runtime": 319.5142,
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- "eval_samples_per_second": 93.893,
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- "eval_steps_per_second": 2.936
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  }
 
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  {
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  "epoch": 3.9936,
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+ "eval_accuracy": 0.9686666666666667,
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+ "eval_loss": 0.11140096187591553,
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+ "eval_runtime": 446.4195,
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+ "eval_samples_per_second": 67.201,
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+ "eval_steps_per_second": 2.101
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  }
eval_results.json CHANGED
@@ -1,8 +1,8 @@
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  {
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  "epoch": 3.9936,
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- "eval_accuracy": 0.9597666666666667,
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- "eval_loss": 0.10777818411588669,
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- "eval_runtime": 319.5142,
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- "eval_samples_per_second": 93.893,
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- "eval_steps_per_second": 2.936
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  }
 
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  {
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  "epoch": 3.9936,
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+ "eval_accuracy": 0.9686666666666667,
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+ "eval_loss": 0.11140096187591553,
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+ "eval_runtime": 446.4195,
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+ "eval_samples_per_second": 67.201,
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+ "eval_steps_per_second": 2.101
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  }