End of training

README.md

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+---
+license: apache-2.0
+base_model: microsoft/beit-large-patch16-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: Boya1_3Class_SGD_1-e3_20Epoch_Beit-large-224_fold1
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: test
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.7654086342655444
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# Boya1_3Class_SGD_1-e3_20Epoch_Beit-large-224_fold1
+
+This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5544
+- Accuracy: 0.7654
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.001
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.9015        | 1.0   | 924   | 0.9341          | 0.6112   |
+| 0.8409        | 2.0   | 1848  | 0.7990          | 0.6780   |
+| 0.787         | 3.0   | 2772  | 0.7073          | 0.7116   |
+| 0.638         | 4.0   | 3696  | 0.6605          | 0.7269   |
+| 0.7348        | 5.0   | 4620  | 0.6355          | 0.7355   |
+| 0.5951        | 6.0   | 5544  | 0.6177          | 0.7396   |
+| 0.6333        | 7.0   | 6468  | 0.6036          | 0.7456   |
+| 0.5506        | 8.0   | 7392  | 0.5938          | 0.7491   |
+| 0.5249        | 9.0   | 8316  | 0.5879          | 0.7526   |
+| 0.7137        | 10.0  | 9240  | 0.5788          | 0.7570   |
+| 0.5106        | 11.0  | 10164 | 0.5775          | 0.7575   |
+| 0.6297        | 12.0  | 11088 | 0.5685          | 0.7608   |
+| 0.5637        | 13.0  | 12012 | 0.5647          | 0.7613   |
+| 0.5879        | 14.0  | 12936 | 0.5617          | 0.7632   |
+| 0.4454        | 15.0  | 13860 | 0.5588          | 0.7649   |
+| 0.522         | 16.0  | 14784 | 0.5607          | 0.7630   |
+| 0.551         | 17.0  | 15708 | 0.5549          | 0.7660   |
+| 0.6177        | 18.0  | 16632 | 0.5560          | 0.7641   |
+| 0.5656        | 19.0  | 17556 | 0.5549          | 0.7641   |
+| 0.6413        | 20.0  | 18480 | 0.5544          | 0.7654   |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.0.1
+- Datasets 2.12.0
+- Tokenizers 0.13.2

config.json

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+{
+  "_name_or_path": "microsoft/beit-large-patch16-224",
+  "architectures": [
+    "BeitForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "auxiliary_channels": 256,
+  "auxiliary_concat_input": false,
+  "auxiliary_loss_weight": 0.4,
+  "auxiliary_num_convs": 1,
+  "drop_path_rate": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "HeadAbnormalities",
+    "1": "NeckAbnormalities",
+    "2": "Normal",
+    "3": "TailAbnormalities"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "label2id": {
+    "HeadAbnormalities": "0",
+    "NeckAbnormalities": "1",
+    "Normal": "2",
+    "TailAbnormalities": "3"
+  },
+  "layer_norm_eps": 1e-12,
+  "layer_scale_init_value": 0.1,
+  "model_type": "beit",
+  "num_attention_heads": 16,
+  "num_channels": 3,
+  "num_hidden_layers": 24,
+  "out_indices": [
+    3,
+    5,
+    7,
+    11
+  ],
+  "patch_size": 16,
+  "pool_scales": [
+    1,
+    2,
+    3,
+    6
+  ],
+  "problem_type": "single_label_classification",
+  "semantic_loss_ignore_index": 255,
+  "torch_dtype": "float32",
+  "transformers_version": "4.32.1",
+  "use_absolute_position_embeddings": false,
+  "use_auxiliary_head": true,
+  "use_mask_token": false,
+  "use_mean_pooling": true,
+  "use_relative_position_bias": true,
+  "use_shared_relative_position_bias": false,
+  "vocab_size": 8192
+}

preprocessor_config.json

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+{
+  "crop_size": {
+    "height": 224,
+    "width": 224
+  },
+  "do_center_crop": false,
+  "do_normalize": true,
+  "do_reduce_labels": false,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_processor_type": "BeitImageProcessor",
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 224,
+    "width": 224
+  }
+}

pytorch_model.bin

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+size 1213789289

training_args.bin

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