End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: microsoft/swin-tiny-patch4-window7-224
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+model-index:
+- name: swin-transformer-results
+  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. -->
+
+# swin-transformer-results
+
+This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8055
+- Accuracy: 0.6794
+- F1: 0.6810
+- Precision: 0.6904
+
+## 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: 2e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|
+| 1.0686        | 0.1952 | 500  | 1.0585          | 0.5266   | 0.5042 | 0.5355    |
+| 1.3283        | 0.3903 | 1000 | 1.0015          | 0.5722   | 0.5794 | 0.6006    |
+| 0.991         | 0.5855 | 1500 | 0.9601          | 0.5828   | 0.5865 | 0.6194    |
+| 0.7919        | 0.7806 | 2000 | 0.9066          | 0.6135   | 0.6191 | 0.6580    |
+| 0.9748        | 0.9758 | 2500 | 0.8327          | 0.6460   | 0.6443 | 0.6458    |
+| 0.7183        | 1.1710 | 3000 | 0.8808          | 0.6421   | 0.6419 | 0.6638    |
+| 0.769         | 1.3661 | 3500 | 0.8454          | 0.6526   | 0.6483 | 0.6553    |
+| 0.8558        | 1.5613 | 4000 | 0.8773          | 0.6482   | 0.6364 | 0.6454    |
+| 0.6713        | 1.7564 | 4500 | 0.8338          | 0.6561   | 0.6560 | 0.6711    |
+| 0.7476        | 1.9516 | 5000 | 0.8083          | 0.6632   | 0.6636 | 0.6690    |
+| 0.6896        | 2.1468 | 5500 | 0.8055          | 0.6794   | 0.6810 | 0.6904    |
+| 0.648         | 2.3419 | 6000 | 0.8252          | 0.6697   | 0.6726 | 0.6822    |
+| 0.5969        | 2.5371 | 6500 | 0.8179          | 0.6697   | 0.6676 | 0.6661    |
+| 0.7098        | 2.7322 | 7000 | 0.8139          | 0.6724   | 0.6705 | 0.6698    |
+| 0.5318        | 2.9274 | 7500 | 0.8033          | 0.6790   | 0.6783 | 0.6793    |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cpu
+- Datasets 3.0.0
+- Tokenizers 0.19.1

all_results.json

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+{
+    "epoch": 3.0,
+    "eval_accuracy": 0.6794027228809838,
+    "eval_f1": 0.6810232542216262,
+    "eval_loss": 0.8055222034454346,
+    "eval_precision": 0.6903667447745538,
+    "eval_runtime": 864.6277,
+    "eval_samples_per_second": 2.634,
+    "eval_steps_per_second": 0.33,
+    "total_flos": 1.5279830292400128e+18,
+    "train_loss": 0.8075623554765263,
+    "train_runtime": 38574.522,
+    "train_samples_per_second": 1.594,
+    "train_steps_per_second": 0.199
+}

config.json

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+{
+  "_name_or_path": "microsoft/swin-tiny-patch4-window7-224",
+  "architectures": [
+    "SwinForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "depths": [
+    2,
+    2,
+    6,
+    2
+  ],
+  "drop_path_rate": 0.1,
+  "embed_dim": 96,
+  "encoder_stride": 32,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "happy",
+    "1": "sad",
+    "2": "angry",
+    "3": "neutral"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "angry": 2,
+    "happy": 0,
+    "neutral": 3,
+    "sad": 1
+  },
+  "layer_norm_eps": 1e-05,
+  "mlp_ratio": 4.0,
+  "model_type": "swin",
+  "num_channels": 3,
+  "num_heads": [
+    3,
+    6,
+    12,
+    24
+  ],
+  "num_layers": 4,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "patch_size": 4,
+  "path_norm": true,
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "torch_dtype": "float32",
+  "transformers_version": "4.44.2",
+  "use_absolute_embeddings": false,
+  "window_size": 7
+}

eval_results.json

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+{
+    "epoch": 3.0,
+    "eval_accuracy": 0.6794027228809838,
+    "eval_f1": 0.6810232542216262,
+    "eval_loss": 0.8055222034454346,
+    "eval_precision": 0.6903667447745538,
+    "eval_runtime": 864.6277,
+    "eval_samples_per_second": 2.634,
+    "eval_steps_per_second": 0.33
+}

model.safetensors

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+oid sha256:184599c33ea8dfc549e3f2298272144331a0e15568fc103666fa79c323ef4db1
+size 110348984

preprocessor_config.json

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+{
+  "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": 224,
+    "width": 224
+  }
+}

train_results.json

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+{
+    "epoch": 3.0,
+    "total_flos": 1.5279830292400128e+18,
+    "train_loss": 0.8075623554765263,
+    "train_runtime": 38574.522,
+    "train_samples_per_second": 1.594,
+    "train_steps_per_second": 0.199
+}

training_args.bin

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+size 5112