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: Chess_images_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: 0.9
+---
+
+<!-- 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. -->
+
+# Chess_images_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: 1.0591
+- Accuracy: 0.9
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 2    | 1.7966          | 0.1      |
+| No log        | 2.0   | 4    | 1.7835          | 0.2      |
+| No log        | 3.0   | 6    | 1.7547          | 0.2667   |
+| No log        | 4.0   | 8    | 1.7069          | 0.3667   |
+| 1.7198        | 5.0   | 10   | 1.6416          | 0.3667   |
+| 1.7198        | 6.0   | 12   | 1.5306          | 0.4      |
+| 1.7198        | 7.0   | 14   | 1.4958          | 0.5333   |
+| 1.7198        | 8.0   | 16   | 1.4440          | 0.5333   |
+| 1.7198        | 9.0   | 18   | 1.3930          | 0.6      |
+| 1.3635        | 10.0  | 20   | 1.2984          | 0.7333   |
+| 1.3635        | 11.0  | 22   | 1.3484          | 0.7333   |
+| 1.3635        | 12.0  | 24   | 1.2727          | 0.8333   |
+| 1.3635        | 13.0  | 26   | 1.1674          | 0.8333   |
+| 1.3635        | 14.0  | 28   | 1.1443          | 0.8667   |
+| 1.0916        | 15.0  | 30   | 1.1607          | 0.9      |
+| 1.0916        | 16.0  | 32   | 1.1076          | 0.8667   |
+| 1.0916        | 17.0  | 34   | 1.0670          | 0.9667   |
+| 1.0916        | 18.0  | 36   | 1.0694          | 0.9333   |
+| 1.0916        | 19.0  | 38   | 1.0874          | 0.9      |
+| 0.9397        | 20.0  | 40   | 1.0591          | 0.9      |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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": "Black king",
+    "1": "Black knight",
+    "2": "Black queen",
+    "3": "White king",
+    "4": "White knight",
+    "5": "White queen"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "Black king": "0",
+    "Black knight": "1",
+    "Black queen": "2",
+    "White king": "3",
+    "White knight": "4",
+    "White queen": "5"
+  },
+  "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": "4.38.2"
+}

model.safetensors

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+size 343236280

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
+  }
+}

runs/Apr04_17-40-50_89459fbb1746/events.out.tfevents.1712252451.89459fbb1746.121.0

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+size 12338

training_args.bin

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