wildfire_classifier

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-384
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: fine_tuned_wildfire
+  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. -->
+
+# fine_tuned_wildfire
+
+This model is a fine-tuned version of [google/vit-base-patch16-384](https://huggingface.co/google/vit-base-patch16-384) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2329
+- Accuracy: 0.9202
+
+## 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
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.1208        | 1.28  | 100  | 0.2329          | 0.9202   |
+| 0.0261        | 2.56  | 200  | 0.2469          | 0.9316   |
+| 0.0007        | 3.85  | 300  | 0.2358          | 0.9392   |
+
+
+### Framework versions
+
+- Transformers 4.33.2
+- Pytorch 2.0.1+cu117
+- Datasets 2.14.5
+- Tokenizers 0.13.3

all_results.json

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+}

config.json

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+{
+  "_name_or_path": "google/vit-base-patch16-384",
+  "architectures": [
+    "ViTForImageClassification"
+  ],
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+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "nofire",
+    "1": "fire"
+  },
+  "image_size": 384,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "fire": 1,
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+  },
+  "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"
+}

eval_results.json

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+}

model.safetensors

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preprocessor_config.json

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+  "do_resize": true,
+  "image_mean": [
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+    0.5
+  ],
+  "image_processor_type": "ViTFeatureExtractor",
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+}

test_results.json

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+}

train_results.json

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+}

trainer_state.json

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