End of training

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: vit-base-images
+  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. -->
+
+# vit-base-images
+
+This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3465
+- Accuracy: 0.905
+
+## 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: 0.0002
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.7334        | 0.4   | 100  | 0.6142          | 0.779    |
+| 0.6032        | 0.8   | 200  | 0.5516          | 0.808    |
+| 0.4725        | 1.2   | 300  | 0.4390          | 0.854    |
+| 0.3638        | 1.6   | 400  | 0.4622          | 0.822    |
+| 0.3279        | 2.0   | 500  | 0.3772          | 0.876    |
+| 0.1337        | 2.4   | 600  | 0.4518          | 0.869    |
+| 0.236         | 2.8   | 700  | 0.3766          | 0.878    |
+| 0.0275        | 3.2   | 800  | 0.3518          | 0.891    |
+| 0.0427        | 3.6   | 900  | 0.3709          | 0.896    |
+| 0.0363        | 4.0   | 1000 | 0.3465          | 0.905    |
+
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.3.1+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

all_results.json

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+    "eval_accuracy": 0.905,
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+    "eval_samples_per_second": 47.074,
+    "eval_steps_per_second": 5.884,
+    "total_flos": 1.239905171570688e+18,
+    "train_loss": 0.3179253642559052,
+    "train_runtime": 607.1163,
+    "train_samples_per_second": 26.354,
+    "train_steps_per_second": 1.647
+}

config.json

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+{
+  "_name_or_path": "google/vit-base-patch16-224-in21k",
+  "architectures": [
+    "ViTForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "encoder_stride": 16,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "basal_cell_carcinoma",
+    "1": "benign_keratosis-like_lesions",
+    "2": "melanocytic_Nevi",
+    "3": "dermatofibroma",
+    "4": "actinic_keratoses"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "actinic_keratoses": "4",
+    "basal_cell_carcinoma": "0",
+    "benign_keratosis-like_lesions": "1",
+    "dermatofibroma": "3",
+    "melanocytic_Nevi": "2"
+  },
+  "layer_norm_eps": 1e-12,
+  "model_type": "vit",
+  "num_attention_heads": 12,
+  "num_channels": 3,
+  "num_hidden_layers": 12,
+  "patch_size": 16,
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.42.4"
+}

eval_results.json

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+}

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preprocessor_config.json

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train_results.json

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