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beit-base-patch16-224

Image Classification
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PyTorch
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beit
Generated from Trainer
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  1. README.md +58 -66
  2. model.safetensors +1 -1
  3. runs/Mar27_15-56-28_dbda3bb1da36/events.out.tfevents.1711554998.dbda3bb1da36.335.1 +2 -2
  4. runs/Mar27_15-56-28_dbda3bb1da36/events.out.tfevents.1711556291.dbda3bb1da36.335.2 +3 -0
README.md CHANGED
@@ -3,34 +3,13 @@ license: apache-2.0
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  base_model: microsoft/beit-base-patch16-224
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  tags:
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  - generated_from_trainer
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- datasets:
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- - imagefolder
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  metrics:
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  - accuracy
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  - precision
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  - recall
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  model-index:
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  - name: beit-base-patch16-224
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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: imagefolder
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- type: imagefolder
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- config: default
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- split: validation
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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: 0.85
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- - name: Precision
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- type: precision
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- value: 0.8455590062111802
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- - name: Recall
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- type: recall
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- value: 0.85
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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
@@ -38,13 +17,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # beit-base-patch16-224
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- This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4871
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- - Accuracy: 0.85
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- - Precision: 0.8456
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- - Recall: 0.85
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- - F1 Score: 0.8464
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  ## Model description
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@@ -64,55 +43,68 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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- - train_batch_size: 64
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- - eval_batch_size: 64
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  - seed: 42
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  - gradient_accumulation_steps: 4
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- - total_train_batch_size: 256
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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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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 30
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  ### Training results
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79
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
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- | No log | 1.0 | 4 | 0.5784 | 0.7333 | 0.5378 | 0.7333 | 0.6205 |
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- | No log | 2.0 | 8 | 0.5813 | 0.7375 | 0.7030 | 0.7375 | 0.6441 |
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- | No log | 3.0 | 12 | 0.5486 | 0.7417 | 0.7297 | 0.7417 | 0.7343 |
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- | No log | 4.0 | 16 | 0.5394 | 0.7542 | 0.7333 | 0.7542 | 0.7370 |
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- | No log | 5.0 | 20 | 0.5067 | 0.775 | 0.7658 | 0.775 | 0.7321 |
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- | No log | 6.0 | 24 | 0.5542 | 0.7958 | 0.7966 | 0.7958 | 0.7613 |
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- | No log | 7.0 | 28 | 0.4753 | 0.7958 | 0.7834 | 0.7958 | 0.7758 |
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- | 0.5325 | 8.0 | 32 | 0.5265 | 0.7792 | 0.7661 | 0.7792 | 0.7448 |
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- | 0.5325 | 9.0 | 36 | 0.4789 | 0.8208 | 0.8134 | 0.8208 | 0.8067 |
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- | 0.5325 | 10.0 | 40 | 0.4939 | 0.7875 | 0.7932 | 0.7875 | 0.7900 |
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- | 0.5325 | 11.0 | 44 | 0.4917 | 0.8042 | 0.8032 | 0.8042 | 0.8037 |
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- | 0.5325 | 12.0 | 48 | 0.5001 | 0.8083 | 0.8019 | 0.8083 | 0.8041 |
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- | 0.5325 | 13.0 | 52 | 0.4742 | 0.8 | 0.7897 | 0.8 | 0.7915 |
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- | 0.5325 | 14.0 | 56 | 0.5439 | 0.7875 | 0.8037 | 0.7875 | 0.7932 |
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- | 0.3381 | 15.0 | 60 | 0.5436 | 0.8333 | 0.8265 | 0.8333 | 0.8263 |
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- | 0.3381 | 16.0 | 64 | 0.4989 | 0.8375 | 0.8312 | 0.8375 | 0.8288 |
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- | 0.3381 | 17.0 | 68 | 0.4949 | 0.8333 | 0.8282 | 0.8333 | 0.8296 |
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- | 0.3381 | 18.0 | 72 | 0.4709 | 0.8292 | 0.8283 | 0.8292 | 0.8287 |
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- | 0.3381 | 19.0 | 76 | 0.4680 | 0.8167 | 0.8133 | 0.8167 | 0.8147 |
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- | 0.3381 | 20.0 | 80 | 0.5053 | 0.8417 | 0.8362 | 0.8417 | 0.8371 |
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- | 0.3381 | 21.0 | 84 | 0.5480 | 0.8458 | 0.8459 | 0.8458 | 0.8322 |
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- | 0.3381 | 22.0 | 88 | 0.4548 | 0.8542 | 0.8512 | 0.8542 | 0.8522 |
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- | 0.2076 | 23.0 | 92 | 0.4891 | 0.8458 | 0.8407 | 0.8458 | 0.8376 |
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- | 0.2076 | 24.0 | 96 | 0.4981 | 0.85 | 0.8486 | 0.85 | 0.8492 |
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- | 0.2076 | 25.0 | 100 | 0.4993 | 0.8458 | 0.8426 | 0.8458 | 0.8438 |
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- | 0.2076 | 26.0 | 104 | 0.5026 | 0.8542 | 0.8503 | 0.8542 | 0.8514 |
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- | 0.2076 | 27.0 | 108 | 0.4944 | 0.8542 | 0.8522 | 0.8542 | 0.8530 |
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- | 0.2076 | 28.0 | 112 | 0.4821 | 0.8542 | 0.8549 | 0.8542 | 0.8545 |
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- | 0.2076 | 29.0 | 116 | 0.4714 | 0.8583 | 0.8559 | 0.8583 | 0.8568 |
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- | 0.138 | 30.0 | 120 | 0.4705 | 0.8583 | 0.8559 | 0.8583 | 0.8568 |
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.33.3
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- - Pytorch 2.0.1+cu118
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- - Datasets 2.14.5
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- - Tokenizers 0.13.3
 
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  base_model: microsoft/beit-base-patch16-224
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  tags:
5
  - generated_from_trainer
 
 
6
  metrics:
7
  - accuracy
8
  - precision
9
  - recall
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  model-index:
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  - name: beit-base-patch16-224
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+ results: []
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
13
  ---
14
 
15
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
17
 
18
  # beit-base-patch16-224
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20
+ This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3575
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+ - Accuracy: 0.9456
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+ - Precision: 0.9498
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+ - Recall: 0.9456
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+ - F1 Score: 0.9473
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28
  ## Model description
29
 
 
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44
  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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  - seed: 42
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  - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
53
  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 45
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  ### Training results
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58
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score |
59
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
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+ | No log | 0.94 | 4 | 0.3212 | 0.8475 | 0.8711 | 0.8475 | 0.7915 |
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+ | No log | 1.88 | 8 | 0.2355 | 0.8983 | 0.8925 | 0.8983 | 0.8937 |
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+ | No log | 2.82 | 12 | 0.3134 | 0.8644 | 0.8834 | 0.8644 | 0.8243 |
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+ | 0.2493 | 4.0 | 17 | 0.2434 | 0.8814 | 0.8962 | 0.8814 | 0.8534 |
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+ | 0.2493 | 4.94 | 21 | 0.3406 | 0.8983 | 0.9094 | 0.8983 | 0.8794 |
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+ | 0.2493 | 5.88 | 25 | 0.1131 | 0.9322 | 0.9300 | 0.9322 | 0.9291 |
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+ | 0.2493 | 6.82 | 29 | 0.1727 | 0.9153 | 0.9435 | 0.9153 | 0.9215 |
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+ | 0.0374 | 8.0 | 34 | 0.6181 | 0.8644 | 0.8834 | 0.8644 | 0.8243 |
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+ | 0.0374 | 8.94 | 38 | 0.3249 | 0.9153 | 0.9125 | 0.9153 | 0.9135 |
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+ | 0.0374 | 9.88 | 42 | 0.5308 | 0.8983 | 0.8934 | 0.8983 | 0.8876 |
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+ | 0.007 | 10.82 | 46 | 0.4767 | 0.9153 | 0.9119 | 0.9153 | 0.9090 |
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+ | 0.007 | 12.0 | 51 | 0.3883 | 0.8983 | 0.8925 | 0.8983 | 0.8937 |
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+ | 0.007 | 12.94 | 55 | 0.3627 | 0.8983 | 0.8934 | 0.8983 | 0.8876 |
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+ | 0.007 | 13.88 | 59 | 0.2783 | 0.9492 | 0.9479 | 0.9492 | 0.9481 |
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+ | 0.0012 | 14.82 | 63 | 0.1934 | 0.9492 | 0.9519 | 0.9492 | 0.9501 |
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+ | 0.0012 | 16.0 | 68 | 0.1670 | 0.9661 | 0.9661 | 0.9661 | 0.9661 |
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+ | 0.0012 | 16.94 | 72 | 0.1783 | 0.9492 | 0.9479 | 0.9492 | 0.9481 |
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+ | 0.0001 | 17.88 | 76 | 0.4825 | 0.9322 | 0.9373 | 0.9322 | 0.9251 |
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+ | 0.0001 | 18.82 | 80 | 0.9010 | 0.8983 | 0.9094 | 0.8983 | 0.8794 |
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+ | 0.0001 | 20.0 | 85 | 0.1802 | 0.9661 | 0.9718 | 0.9661 | 0.9673 |
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+ | 0.0001 | 20.94 | 89 | 0.5658 | 0.9153 | 0.9119 | 0.9153 | 0.9090 |
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+ | 0.0037 | 21.88 | 93 | 0.8331 | 0.9322 | 0.9373 | 0.9322 | 0.9251 |
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+ | 0.0037 | 22.82 | 97 | 0.8074 | 0.9153 | 0.9119 | 0.9153 | 0.9090 |
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+ | 0.0037 | 24.0 | 102 | 0.4763 | 0.8814 | 0.8771 | 0.8814 | 0.8788 |
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+ | 0.0002 | 24.94 | 106 | 0.5553 | 0.9153 | 0.9119 | 0.9153 | 0.9090 |
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+ | 0.0002 | 25.88 | 110 | 0.8220 | 0.9153 | 0.9231 | 0.9153 | 0.9032 |
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+ | 0.0002 | 26.82 | 114 | 0.5367 | 0.9322 | 0.9373 | 0.9322 | 0.9251 |
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+ | 0.0002 | 28.0 | 119 | 0.4401 | 0.9153 | 0.9298 | 0.9153 | 0.9194 |
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+ | 0.0037 | 28.94 | 123 | 0.4138 | 0.9153 | 0.9125 | 0.9153 | 0.9135 |
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+ | 0.0037 | 29.88 | 127 | 0.7232 | 0.8983 | 0.9094 | 0.8983 | 0.8794 |
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+ | 0.0037 | 30.82 | 131 | 0.3690 | 0.9322 | 0.9373 | 0.9322 | 0.9251 |
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+ | 0.0115 | 32.0 | 136 | 0.2730 | 0.9322 | 0.9400 | 0.9322 | 0.9346 |
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+ | 0.0115 | 32.94 | 140 | 0.2101 | 0.9661 | 0.9661 | 0.9661 | 0.9661 |
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+ | 0.0115 | 33.88 | 144 | 0.1814 | 0.9661 | 0.9661 | 0.9661 | 0.9661 |
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+ | 0.0115 | 34.82 | 148 | 0.1641 | 0.9661 | 0.9661 | 0.9661 | 0.9661 |
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+ | 0.0013 | 36.0 | 153 | 0.1600 | 0.9492 | 0.9479 | 0.9492 | 0.9481 |
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+ | 0.0013 | 36.94 | 157 | 0.1709 | 0.9661 | 0.9674 | 0.9661 | 0.9646 |
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+ | 0.0013 | 37.88 | 161 | 0.1913 | 0.9661 | 0.9674 | 0.9661 | 0.9646 |
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+ | 0.0001 | 38.82 | 165 | 0.2047 | 0.9661 | 0.9674 | 0.9661 | 0.9646 |
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+ | 0.0001 | 40.0 | 170 | 0.2030 | 0.9661 | 0.9674 | 0.9661 | 0.9646 |
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+ | 0.0001 | 40.94 | 174 | 0.1960 | 0.9661 | 0.9674 | 0.9661 | 0.9646 |
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+ | 0.0001 | 41.88 | 178 | 0.1936 | 0.9661 | 0.9674 | 0.9661 | 0.9646 |
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+ | 0.0003 | 42.35 | 180 | 0.1934 | 0.9661 | 0.9674 | 0.9661 | 0.9646 |
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  ### Framework versions
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+ - Transformers 4.38.2
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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