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
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: vit-dunham-carbonate-classifier
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8888888888888888
+---
+
+<!-- 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-dunham-carbonate-classifier
+
+This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7676
+- Accuracy: 0.8889
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.5764        | 1.0   | 5    | 1.5329          | 0.4444   |
+| 1.3991        | 2.0   | 10   | 1.4253          | 0.5556   |
+| 1.2792        | 3.0   | 15   | 1.2851          | 0.7778   |
+| 1.0119        | 4.0   | 20   | 1.1625          | 0.8889   |
+| 0.9916        | 5.0   | 25   | 1.0471          | 0.8889   |
+| 0.9202        | 6.0   | 30   | 0.9836          | 0.7778   |
+| 0.6994        | 7.0   | 35   | 0.8649          | 0.8889   |
+| 0.526         | 8.0   | 40   | 0.7110          | 1.0      |
+| 0.5383        | 9.0   | 45   | 0.6127          | 1.0      |
+| 0.5128        | 10.0  | 50   | 0.5337          | 1.0      |
+| 0.4312        | 11.0  | 55   | 0.4887          | 1.0      |
+| 0.3827        | 12.0  | 60   | 0.4365          | 1.0      |
+| 0.3452        | 13.0  | 65   | 0.3891          | 1.0      |
+| 0.3164        | 14.0  | 70   | 0.3677          | 1.0      |
+| 0.2899        | 15.0  | 75   | 0.3555          | 1.0      |
+| 0.2878        | 16.0  | 80   | 0.3197          | 1.0      |
+| 0.2884        | 17.0  | 85   | 0.3056          | 1.0      |
+| 0.2633        | 18.0  | 90   | 0.3107          | 1.0      |
+| 0.2669        | 19.0  | 95   | 0.3164          | 1.0      |
+| 0.2465        | 20.0  | 100  | 0.2949          | 1.0      |
+
+
+### Framework versions
+
+- Transformers 4.33.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3

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": "Crystalline",
+    "1": "Grainstone",
+    "2": "Mudstone",
+    "3": "Packstone",
+    "4": "Wackestone"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "Crystalline": "0",
+    "Grainstone": "1",
+    "Mudstone": "2",
+    "Packstone": "3",
+    "Wackestone": "4"
+  },
+  "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": "4.33.2"
+}

preprocessor_config.json

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+{
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_processor_type": "ViTImageProcessor",
+  "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 343277933

training_args.bin

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