End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google/vit-base-patch16-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+model-index:
+- name: vit-base-patch16-224-finetuned-eurosat
+  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-patch16-224-finetuned-eurosat
+
+This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- eval_loss: 2.4052
+- eval_model_preparation_time: 0.0118
+- eval_accuracy: 0.1337
+- eval_runtime: 253.0403
+- eval_samples_per_second: 10.67
+- eval_steps_per_second: 0.336
+- step: 0
+
+## 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
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3
+
+### Framework versions
+
+- Transformers 4.45.2
+- Pytorch 2.4.1
+- Datasets 3.0.1
+- Tokenizers 0.20.1

all_results.json

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+{
+    "eval_accuracy": 0.1337037037037037,
+    "eval_loss": 2.4051928520202637,
+    "eval_model_preparation_time": 0.0118,
+    "eval_runtime": 253.0403,
+    "eval_samples_per_second": 10.67,
+    "eval_steps_per_second": 0.336
+}

config.json

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+{
+  "_name_or_path": "google/vit-base-patch16-224",
+  "architectures": [
+    "ViTForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "encoder_stride": 16,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "AnnualCrop",
+    "1": "Forest",
+    "2": "HerbaceousVegetation",
+    "3": "Highway",
+    "4": "Industrial",
+    "5": "Pasture",
+    "6": "PermanentCrop",
+    "7": "Residential",
+    "8": "River",
+    "9": "SeaLake"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "AnnualCrop": 0,
+    "Forest": 1,
+    "HerbaceousVegetation": 2,
+    "Highway": 3,
+    "Industrial": 4,
+    "Pasture": 5,
+    "PermanentCrop": 6,
+    "Residential": 7,
+    "River": 8,
+    "SeaLake": 9
+  },
+  "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": "4.45.2"
+}

eval_results.json

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+{
+    "eval_accuracy": 0.1337037037037037,
+    "eval_loss": 2.4051928520202637,
+    "eval_model_preparation_time": 0.0118,
+    "eval_runtime": 253.0403,
+    "eval_samples_per_second": 10.67,
+    "eval_steps_per_second": 0.336
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:2610c0ea77579b319c687b04e82cff1cfcffd328b26ef072784ca223047f269f
+size 343248584

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
+  }
+}

training_args.bin

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+size 5240