End of training

README.md

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+---
+license: apache-2.0
+base_model: microsoft/swinv2-base-patch4-window16-256
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: SwinV2-Base-Document-Classifier
+  results: []
+---
+
+<!-- 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. -->
+
+# SwinV2-Base-Document-Classifier
+
+This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window16-256](https://huggingface.co/microsoft/swinv2-base-patch4-window16-256) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0573
+- Accuracy: 0.9810
+- F1: 0.9810
+- Precision: 0.9813
+- Recall: 0.9810
+
+## 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: 5e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- training_steps: 400
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.0814        | 0.12  | 50   | 0.0876          | 0.9740   | 0.9741 | 0.9749    | 0.9740 |
+| 0.078         | 0.13  | 51   | 0.0658          | 0.9797   | 0.9797 | 0.9799    | 0.9797 |
+| 0.143         | 0.13  | 52   | 0.0609          | 0.9831   | 0.9831 | 0.9832    | 0.9831 |
+| 0.0863        | 0.13  | 53   | 0.0595          | 0.9832   | 0.9832 | 0.9834    | 0.9832 |
+| 0.0561        | 0.14  | 54   | 0.0650          | 0.9825   | 0.9825 | 0.9826    | 0.9825 |
+| 0.1118        | 0.14  | 55   | 0.0697          | 0.9804   | 0.9804 | 0.9806    | 0.9804 |
+| 0.1258        | 0.14  | 56   | 0.1053          | 0.9678   | 0.9678 | 0.9697    | 0.9678 |
+| 0.132         | 0.14  | 57   | 0.0672          | 0.9781   | 0.9781 | 0.9785    | 0.9781 |
+| 0.1564        | 0.14  | 58   | 0.0582          | 0.9827   | 0.9827 | 0.9829    | 0.9827 |
+| 0.1085        | 0.15  | 59   | 0.0557          | 0.9849   | 0.9848 | 0.9849    | 0.9848 |
+| 0.0506        | 0.15  | 60   | 0.0548          | 0.9845   | 0.9845 | 0.9845    | 0.9845 |
+| 0.0787        | 0.15  | 61   | 0.1049          | 0.9660   | 0.9661 | 0.9681    | 0.9660 |
+| 0.1211        | 0.15  | 62   | 0.0792          | 0.9741   | 0.9741 | 0.9746    | 0.9741 |
+| 0.0907        | 0.16  | 63   | 0.0608          | 0.9826   | 0.9825 | 0.9826    | 0.9826 |
+| 0.0419        | 0.16  | 64   | 0.0577          | 0.9832   | 0.9832 | 0.9833    | 0.9832 |
+| 0.1659        | 0.16  | 65   | 0.0548          | 0.9843   | 0.9843 | 0.9844    | 0.9843 |
+| 0.0983        | 0.17  | 66   | 0.0657          | 0.9805   | 0.9805 | 0.9814    | 0.9804 |
+| 0.0535        | 0.17  | 67   | 0.0493          | 0.9851   | 0.9851 | 0.9851    | 0.9851 |
+| 0.0936        | 0.17  | 68   | 0.0588          | 0.9827   | 0.9827 | 0.9830    | 0.9827 |
+| 0.0933        | 0.17  | 69   | 0.0573          | 0.9810   | 0.9810 | 0.9813    | 0.9810 |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.2.2
+- Datasets 2.18.0
+- Tokenizers 0.15.2

config.json

@@ -0,0 +1,73 @@
+{
+  "_name_or_path": "microsoft/swinv2-base-patch4-window16-256",
+  "architectures": [
+    "Swinv2ForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "depths": [
+    2,
+    2,
+    18,
+    2
+  ],
+  "drop_path_rate": 0.1,
+  "embed_dim": 128,
+  "encoder_stride": 32,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "Barcode",
+    "1": "Invoice",
+    "2": "Object",
+    "3": "Receipt",
+    "4": "Non-Object"
+  },
+  "image_size": 256,
+  "initializer_range": 0.02,
+  "label2id": {
+    "Barcode": 0,
+    "Invoice": 1,
+    "Non-Object": 4,
+    "Object": 2,
+    "Receipt": 3
+  },
+  "layer_norm_eps": 1e-05,
+  "mlp_ratio": 4.0,
+  "model_type": "swinv2",
+  "num_channels": 3,
+  "num_heads": [
+    4,
+    8,
+    16,
+    32
+  ],
+  "num_layers": 4,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "patch_size": 4,
+  "path_norm": true,
+  "pretrained_window_sizes": [
+    0,
+    0,
+    0,
+    0
+  ],
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "torch_dtype": "float32",
+  "transformers_version": "4.39.3",
+  "use_absolute_embeddings": false,
+  "window_size": 16
+}

model.safetensors

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+oid sha256:b02ae140cf170025a29d1da8a8a89ab609c28f413b32d879da6c5e2719f58c73
+size 347657788

preprocessor_config.json

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+{
+  "_valid_processor_keys": [
+    "images",
+    "do_resize",
+    "size",
+    "resample",
+    "do_rescale",
+    "rescale_factor",
+    "do_normalize",
+    "image_mean",
+    "image_std",
+    "return_tensors",
+    "data_format",
+    "input_data_format"
+  ],
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ViTImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 256,
+    "width": 256
+  }
+}

training_args.bin

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