./wmc_v2_vit_base_wm811k_cls_contra_learning_0916

README.md

@@ -4,6 +4,11 @@ license: apache-2.0
 base_model: google/vit-base-patch16-224
 tags:
 - generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
 model-index:
 - name: wmc_v2_vit_base_wm811k_cls_contra_learning_0916
   results: []
@@ -15,6 +20,12 @@ should probably proofread and complete it, then remove this comment. -->
 # wmc_v2_vit_base_wm811k_cls_contra_learning_0916
 
 This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1552
+- Accuracy: 0.9504
+- Precision: 0.9212
+- Recall: 0.9099
+- F1: 0.9116
 
 ## Model description
 
@@ -34,16 +45,27 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 8
-- eval_batch_size: 8
+- train_batch_size: 32
+- eval_batch_size: 32
 - seed: 42
 - gradient_accumulation_steps: 4
-- total_train_batch_size: 32
+- total_train_batch_size: 128
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - num_epochs: 1
 - mixed_precision_training: Native AMP
 
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 1.2292        | 0.1697 | 100  | 0.5873          | 0.8030   | 0.6718    | 0.6428 | 0.6221 |
+| 0.7744        | 0.3394 | 200  | 0.3258          | 0.8962   | 0.8629    | 0.7596 | 0.7444 |
+| 0.6117        | 0.5091 | 300  | 0.1904          | 0.9458   | 0.9262    | 0.8588 | 0.8734 |
+| 0.4829        | 0.6788 | 400  | 0.1799          | 0.9451   | 0.9028    | 0.9129 | 0.9037 |
+| 0.4838        | 0.8485 | 500  | 0.1552          | 0.9504   | 0.9212    | 0.9099 | 0.9116 |
+
+
 ### Framework versions
 
 - Transformers 4.44.2

model.safetensors

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training_args.bin

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