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End of training

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  1. README.md +30 -39
  2. all_results.json +6 -6
  3. eval_results.json +6 -6
  4. model.safetensors +1 -1
README.md CHANGED
@@ -3,26 +3,11 @@ 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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- datasets:
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- - image_folder
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  metrics:
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  - accuracy
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  model-index:
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  - name: results
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- results:
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- - task:
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- name: Image Classification
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- type: image-classification
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- dataset:
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- name: image_folder
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- type: image_folder
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- config: default
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- split: train
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- args: default
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- metrics:
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- - name: Accuracy
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- type: accuracy
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- value: 0.9944991748762314
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -30,10 +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 the image_folder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0158
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- - Accuracy: 0.9945
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  ## Model description
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@@ -65,28 +50,34 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.6956 | 0.26 | 100 | 0.6719 | 0.5956 |
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- | 0.6424 | 0.51 | 200 | 0.5992 | 0.7267 |
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- | 0.5465 | 0.77 | 300 | 0.4793 | 0.7968 |
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- | 0.4107 | 1.02 | 400 | 0.3361 | 0.8649 |
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- | 0.2488 | 1.28 | 500 | 0.1690 | 0.9398 |
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- | 0.1441 | 1.54 | 600 | 0.0882 | 0.9688 |
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- | 0.0945 | 1.79 | 700 | 0.0595 | 0.9809 |
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- | 0.0713 | 2.05 | 800 | 0.0467 | 0.9835 |
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- | 0.0472 | 2.3 | 900 | 0.0320 | 0.9895 |
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- | 0.0411 | 2.56 | 1000 | 0.0260 | 0.9917 |
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- | 0.0302 | 2.82 | 1100 | 0.0241 | 0.9918 |
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- | 0.0259 | 3.07 | 1200 | 0.0192 | 0.9934 |
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- | 0.0197 | 3.33 | 1300 | 0.0157 | 0.9953 |
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- | 0.018 | 3.58 | 1400 | 0.0146 | 0.9950 |
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- | 0.0164 | 3.84 | 1500 | 0.0158 | 0.9945 |
 
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.37.0
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  - Pytorch 2.1.2
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- - Datasets 2.1.0
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- - Tokenizers 0.15.1
 
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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:
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  - accuracy
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  model-index:
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  - name: results
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+ results: []
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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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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  ### Training results
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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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+ - Transformers 4.41.2
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  - Pytorch 2.1.2
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+ - Datasets 2.19.2
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+ - Tokenizers 0.19.1
all_results.json CHANGED
@@ -1,8 +1,8 @@
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  {
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- "epoch": 3.99,
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- "eval_accuracy": 0.9944991748762314,
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- "eval_loss": 0.015824124217033386,
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- "eval_runtime": 115.2936,
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- "eval_samples_per_second": 173.444,
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- "eval_steps_per_second": 5.421
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  }
 
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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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  }
eval_results.json CHANGED
@@ -1,8 +1,8 @@
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  {
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- "epoch": 3.99,
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- "eval_accuracy": 0.9944991748762314,
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- "eval_loss": 0.015824124217033386,
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- "eval_runtime": 115.2936,
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- "eval_samples_per_second": 173.444,
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- "eval_steps_per_second": 5.421
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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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